62 skills found · Page 1 of 3
Tencent / Behaviacbehaviac is a framework of the game AI development, and it also can be used as a rapid game prototype design tool. behaviac supports the behavior tree, finite state machine and hierarchical task network(BT, FSM, HTN)
gdquest-demos / Godot 2d Space GameA 2D space exploration and mining game made with Godot and our AI framework
Juanhacker051 / FOTOSPLOIT *FotoSploit* $ git clone https://github.com/Cesar-Hack-Gray/FotoSploit $ cd FotoSploit $ chmod +x * $ bash install sh $ ./FotoSploit $ show options ================================================= *instalar metasploit no termux(Facilmente)* comandos para instalar metasploit no termux 1: apt update && apt upgrade 2: apt install curl 3: curl -LO https://raw.githubusercontent.com/Hax4us/Metasploit_termux/master/metasploit.sh 4: ls 5: chmod 777 metasploit.sh 6: ls 7: ./metasploit.sh (Carregandooooo) 8: msfconsole ================================================= *EchoPwn* Instalação git clone https://github.com/hackerspider1/EchoPwn.git cd EchoPwn chmod +x install.sh EchoPwn.sh ./install.sh EchoPwn.sh ================================================= *DarkFly-Tool* Instalação apt update && apt upgrade apt install git git clone https://github.com/Ranginang67/DarkFly-Tool cd DarkFly-Tool chmod +x * python2 install.py ================================================= *Tool-x* Instalação apt update apt install git git clone https://github.com/rajkumardusad/Tool-X.git cd Tool-X chmod +x install.aex sh install.aex ou ./install.aex ================================================= *Multi_Phish* pkg instalar droplet pkg instalar openssh pkg instalar git pkg instalar curl pkg instalar wget apt instalar git php -y git clone https://github.com/perjayro/MultiPhish.git cd phish chmod 777 phish.sh bash phish.sh ================================================= *Pentest Tools Framework* git clone https://github.com/pikpikcu/Pentest-Tools-Framework.git cd Pentest-Tools-Framework pip install -r require.txt python install.py python ptf.py ================================================= *Destroyer-framework* ⭕️LINUX git clone https://github.com/Cesar-Hack-Gray/Destroyer-framework cd Destroyer-framework ls bash install.sh ./Destroyer ⭕️TERMUX apt upgrede -y && pkg update -y apt install -y apt install -y curl apt install git git clone https://github.com/Cesar-Hack-Gray/Destroyer-framework cd Destroyer-framework ls bash install.sh ./Destroyer ================================================= *NIKTO* Instalação git clone https://github.com/sullo/nikto apt-get install openssl libcrypt-ssleay-perl Uso de proxys: perl nikto.pl -h localhost -p 8080 -useproxy proxyIp Atualizando Nikto: perl nikto.pl -update ================================================= *SocialFish* Instalação $ apt update && upgrade $ apt install git $ apt install python2 $ git clone https://github.com/UndeadSec/SocialFish.git $ cd SocialFish $ chmod +x * $ pip2 install -r requirements.txt ================================================= *Opal [ATUALIZADO]* git clone https://github.com/shadowlabscc/ProjectOpal.git cd ProjectOpal python opal.py python Injector.py ================================================= *Kit de ferramentas para bugbounty. #CVEs* https://github.com/Medicean/VulApps https://github.com/qazbnm456/awesome-cve-poc https://github.com/tunz/js-vuln-db https://github.com/cve-search/cve-search https://github.com/nixawk/labs https://github.com/Coalfire-Research/java-deserialization-exploits https://github.com/Metnew/uxss-db https://github.com/TH3xACE/SUDO_KILLER https://github.com/Mr-xn/Penetration_Testing_POC https://github.com/toolswatch/vFeed ================================================= *Para pegar informações* 1️⃣ Phone In Foga https://github.com/sundowndev/PhoneInfoga 2️⃣ In Foga - Email https://github.com/m4ll0k/Infoga 3️⃣ Angry Fuzz3r https://github.com/ihebski/angryFuzzer 4️⃣ Hakku Framework https://github.com/4shadoww/hakkuframework 5️⃣ Knock Mail https://github.com/4w4k3/KnockMail 6️⃣ Santet Online https://github.com/Gameye98/santet-online 7️⃣ The Harvester https://github.com/laramies/theHarvester 8️⃣ Optiva Framework https://github.com/joker25000/Optiva-Framework 9️⃣ Cyber Scan https://github.com/medbenali/CyberScan 🔟 Gloom Framework https://github.com/StreetSec/Gloom-Framework ================================================= *OXID Tools* git clone https://github.com/oxyda-fox/OXIDTools.git cd OXIDTools chmod +x * . /setup.sh . /run.sh ================================================= *xShock* Instalação git clone https://github.com/capture0x/xShock/ cd xShock pip3 install -r requirements.txt Executar python3 main.py ================================================= *Web Pentest* Instalação apt update && apt upgrade apt install git apt install python2 apt install python git clone https://github.com/cr4shcod3/pureblood cd pureblood chmod +x * pip install -r requirements.txt Uso python2 pureblood.py ================================================= *Quack* Requisitos apt update && apt upgrade -y termux-setup-storage pkg install -y git pkg install -y python pip install --upgrade pip pip install requests Instalação git clone https://github.com/entynetproject/quack cd quack pip install -r requirements.txt chmod +x quack ================================================= *Thoron Framework* git clone https://github.com/entynetproject/thoron.git cd thoron chmod + x install.sh ./install.sh ================================================= *BlackPhish* git clone https://github.com/Ahmedmahmed8a/BlackPhish cd BlackPhish bash installer.sh ================================================= *RapidPayload* git clone https://github.com/AngelSecurityTeam/RapidPayload cd RapidPayload bash install.sh python3 RapidPayload.py ================================================= *Termux_ExtraKeys* apt update && apt upgrade -y apt install git -y git clone https://github.com/Fabrix07Hack/Termux_ExtraKeys.git cd Termux_ExtraKeys chmod 777 * ./extrakeys_Termux ================================================= *PyReconExSploit* apt-get update apt-get upgrade apt-get install exploitdb netcat nmap perl php git clone https://github.com/AkutoSai/PyReconExSploit cd PyReconExSploit/ python3 setup.py install cp -r /home/user/Desktop/PyReconExSploit/pyreconexsploit /usr/local/lib/python3.7/dist-packages pyreconexsploit ================================================= *Evil Framework* apt update apt upgrade pip2 install requests git clone https://github.com/LOoLzeC/Evil-create-framework cd Evil-create-framework python2 vcrt.py show android help Escolha um virus create virus"seu virus" SET OUTPUT cd /sdcard SET VIRUS NAME "nome do seu virus" run ================================================= *Wifite* apt update && apt upgrade apt install git apt install python2 git clone https://github.com/derv82/wifite2 ls cd wifite ls python2 wifite.py ================================================= *MALICIOUS* $ termux-setup-storage $ cd /sdcard $ apt install git $ apt install python2 $ apt install ruby $ gem install lolcat $ git clone https://github.com/Hider5/Malicious $ cd Malicious $ pip2 install -r requirements.txt $ python2 malicious.py ================================================= *Hammer* apt update apt-get install python -y apt install git apt install python3 git clone https://github.com/cyweb/hammer ls cd hammer chmod +x hammer.py python3 hammer.py -s (alvo) -p 80 -t 150 ================================================= *VIRUS X* $ apt update && apt upgrade $ apt install git $ apt install python $ git clone https://github.com/TSMaitry/VirusX.git $ cd VirusX $ chmod +x VirusX.py $ python2 VirusX.py ================================================= *INFECT* $ apt-get update -y $ apt-get upgrade -y $ apt install python -y $ apt install python2 -y $ apt install git -y $ pip install lolcat $ git clone https://github.com/noob-hackers/Infect $ ls $ cd infect $ ls $ bash infect.sh ================================================= *F-Society Framework* (Instalação) apt install git apt install python2 (Instalação do pacote) git clone https://github.com/Manisso/fsociety ls cd fsociety ls chmod +x fsociety.py ./install.sh python2 fsociety.py ================================================= *MyServer* Abra o termux e digite os seguintes comandos. apt update apt install git git clone https://github.com/rajkumardusad/MyServer cd MyServer chmod +x install ./install ================================================= *AirCrack-ng* apt update apt install root-repo apt install aircrack-ng ================================================= *RouterSploit* apt update && apt upgrade apt install python -y pip2 install apt install git git clone https://github.com/threat9/routersploit ls cd routersploit pip2 install -r requirements -dev.txt pip install future ls python rsf.py ================================================= *Shell Phish* apt update apt upgrade -y termux-setup-storage apt installl git git clone https://github.com/thelinuxchoice/shellphish cd shellphish apt installl php apt install curl git clone https://github.com/PSecurity/ps.ngrok cd ps.ngrok mv ngrok /data/data/com.termux/files/home/shellphish/ cd .. rm -rf ps.ngrok chmod +x ngrok chmod +x shellphish.sh bash shellphish.sh # Ao Iniciar: cd shellphish bash shellphish.sh comandos : pkg install clang git clone https://github.com/XCHADXFAQ77X/XERXES ls cd XERXES ls chmod +x * ls clang xerxes.c -o xerxes ./xerxes exemplo: website.com.br 80 galera lembrando nao bote HTTPS nem www so o nome do site exemplo : website.com.br ``` ALGUNS COMANDOS DO TERMUX BY: BAN``` apt update && apt upgrade termux-setup-storage apt install git apt install net-tools apt install termux-tools apt install neofetch apt install ncurses-utils apt install curl curl -LO https://raw.githubusercontent.com/Hax4us/Metasploit_termux/master/metasploit.sh chmod +x metasploit.sh ./metasploit.sh msfconsole ____________________________________________ https://github.com/PSecurity/ps.ngrok termux-setup-storage apt update && apt upgrade -y pkg update && pkg upgrade -y apt install curl pkg install git git clone https://github.com/PSecurity/ps.ngrok cd ps.ngrok mv ngrok /data/data/com.termux/files/home cd .. chmod +x ngrok ./ngrok ( chave de ativação NGROK) ./ngrok http 80 ________________________________________________ apt update Apt install python2 Apt install git Git clone https://github.com/evait-security/weeman ls cd weeman chmod +x * python2 weeman.py Set url (url) set action_url (url) run (→Abra outra página←) cd .. ./ngrok http 8080 ____________________________________________ apt update apt upgrade apt git git clone https://github.com/liorvh/hammer-1 cd hammer-1 chmod +x * python hammer.py python hammer.py -s (site + www) -t 256 -p 80 ___________________________________________________ apt install git Pkg install clang Faça a instalação do Script git clone https://github.com/zanyarjamal/xerxes Entre no diretório cd xerxes Digite o comando clang xerxes.c -o xerxes Agora e só inicia o Ataque ./xerxes website.com 80 ____________________________________________ apt update && apt upgrade apt install php apt install python2 apt install toilet apt install git git clone https://github.com/4L13199/LITESPAM cd LITESPAM ls sh LITESPAM.sh As opções aparecerão como mostrado abaixo, você apenas escolhe qual bomba de spam SMS será executada ____________________________________________ $ pkg update $ pkg upgrade $ pkg install git $ pkg install php $ pkg install toilet $ pkg install python2 $ gem install lolcat $ pip2 install requests $ pip2 install termcolor $ git clone https://github.com/mbest99/MIXINGS.git $ cd MIXINGS $ bash 0ppay.sh Features:- [ 1] PHISING V1 [ 2] PHISING V2 [ 3] PHISING V3 [ 4] PHISING V4 [ 5] PHISING GAME [ 6] Hack fb target [ 7] Hack fb massal [ 8] Hack fb Target+Massal [ 9] Hack FB ans (#root) [10] Hack Instagram (#root) [11] Hack Twitter (#root) [12] Hack Gmail (#root) [13] Fb Info [14] Santet Online [15] Spam IG [16] Spam WA [17] Spam Sms [18] Youtube AutoView (#root) ____________________________________________ No termux, pra adiantar... pkg install nodejs Em seguida, crie um aplicativo e guarde o nome dele https://www.heroku.com/ $ pkg install git -y $ termux-setup-storage $ ls $ git clone -b herooku https://github.com/XploitWizer/XploitSPY $ cd XploitSPY $ ls $ pkg install nodejs $ npm install heroku -g $ heroku login -i $ heroku git:remote -a nomedoapp $ heroku buildpacks:add heroku/jvm $ heroku buildpacks:add heroku/nodejs $ git push heroku herooku:master ____________________________________________ PERSONALIZAR TERMUX apt update && apt upgrade -y pkg install nano pkg install vim cd ../usr/etc ls vim bash.bashrc Precione a letra (I) para editar o texto Depois vc apaga a seguinte mensagem que aparece no termux " PS1='\$ ' " E cola isso → PS1="\033[1;32m ╔\033[0m""\033[1;31m[ \033m""\033[1;32m SEU NOME AKI\033[0m""\033[1;31m @\033[0m""\033[1;32m║\033[0m""\033[1;37m ≡≡≡≡≡≡≡≡≡≡≡≡≡≡≡\033[0m""\033[1;32m ╚▶ " Coloca o seu nome onde tá escrito " seu nome aqui" Para sair vc clica no ESC + : + x aí você dê enter. Depois de o comando exit e dê enter, dps é só abrir dnovo ;> ____________________________________________ pkg update && pkg upgrade $pkg install python2 $pip2 install requests $pip2 install mechanize $pkg install git $git clone https://github.com/ARIYA-CYBER/NEW $cd NEW $python2 FbNew.py ____________________________________________ https://github.com/Paxv28/CrusherDDoS apt install git apt install python cd CrusherDDoS chmod +x Setup.sh ./Setup.sh python CSDDoS.py
f15gdsy / BT FrameworkBT Framework is a behavior tree framework that can be used to create game AI. It's written for Unity3d.
hagameai / HagamesaiHAGAMEAI is a training framework for AI game evolution.
WahahaYes / GdPlanningAIAn advanced game AI framework, based on Goal Oriented Action Planning (GOAP), and implemented in Godot.
aigamedev / ResistanceFramework for THE RESISTANCE board & card game, with various AI bots.
Qinqing1999 / Yolov5 Tensorrt AimbotFPS game AI aimassist framework
sanusanth / C Basic ProgramsWhat is C#? C# is pronounced "C-Sharp". It is an object-oriented programming language created by Microsoft that runs on the .NET Framework. C# has roots from the C family, and the language is close to other popular languages like C++ and Java. The first version was released in year 2002. The latest version, C# 8, was released in September 2019. C# is a modern object-oriented programming language developed in 2000 by Anders Hejlsberg, the principal designer and lead architect at Microsoft. It is pronounced as "C-Sharp," inspired by the musical notation “♯” which stands for a note with a slightly higher pitch. As it’s considered an incremental compilation of the C++ language, the name C “sharp” seemed most appropriate. The sharp symbol, however, has been replaced by the keyboard friendly “#” as a suffix to “C” for purposes of programming. Although the code is very similar to C++, C# is newer and has grown fast with extensive support from Microsoft. The fact that it’s so similar to Java syntactically helps explain why it has emerged as one of the most popular programming languages today. C# is pronounced "C-Sharp". It is an object-oriented programming language created by Microsoft that runs on the .NET Framework. C# has roots from the C family, and the language is close to other popular languages like C++ and Java. The first version was released in year 2002. The latest version, C# 8, was released in September 2019. C# is used for: Mobile applications Desktop applications Web applications Web services Web sites Games VR Database applications And much, much more! An Introduction to C# Programming C# is a general-purpose, object-oriented programming language that is structured and easy to learn. It runs on Microsoft’s .Net Framework and can be compiled on a variety of computer platforms. As the syntax is simple and easy to learn, developers familiar with C, C++, or Java have found a comfort zone within C#. C# is a boon for developers who want to build a wide range of applications on the .NET Framework—Windows applications, Web applications, and Web services—in addition to building mobile apps, Windows Store apps, and enterprise software. It is thus considered a powerful programming language and features in every developer’s cache of tools. Although first released in 2002, when it was introduced with .NET Framework 1.0, the C# language has evolved a great deal since then. The most recent version is C# 8.0, available in preview as part of Visual Studio. To get access to all of the new language features, you would need to install the latest preview version of .NET Core 3.0. C# is used for: Mobile applications Desktop applications Web applications Web services Web sites Games VR Database applications And much, much more! Why Use C#? It is one of the most popular programming language in the world It is easy to learn and simple to use It has a huge community support C# is an object oriented language which gives a clear structure to programs and allows code to be reused, lowering development costs. As C# is close to C, C++ and Java, it makes it easy for programmers to switch to C# or vice versa. The C# Environment You need the .NET Framework and an IDE (integrated development environment) to work with the C# language. The .NET Framework The .NET Framework platform of the Windows OS is required to write web and desktop-based applications using not only C# but also Visual Basic and Jscript, as the platform provides language interoperability. Besides, the .Net Framework allows C# to communicate with any of the other common languages, such as C++, Jscript, COBOL, and so on. IDEs Microsoft provides various IDEs for C# programming: Visual Studio 2010 (VS) Visual Studio Express Visual Web Developer Visual Studio Code (VSC) The C# source code files can be written using a basic text editor, like Notepad, and compiled using the command-line compiler of the .NET Framework. Alternative open-source versions of the .Net Framework can work on other operating systems as well. For instance, the Mono has a C# compiler and runs on several operating systems, including Linux, Mac, Android, BSD, iOS, Windows, Solaris, and UNIX. This brings enhanced development tools to the developer. As C# is part of the .Net Framework platform, it has access to its enormous library of codes and components, such as Common Language Runtime (CLR), the .Net Framework Class Library, Common Language Specification, Common Type System, Metadata and Assemblies, Windows Forms, ASP.Net and ASP.Net AJAX, Windows Workflow Foundation (WF), Windows Communication Foundation (WCF), and LINQ. C# and Java C# and Java are high-level programming languages that share several similarities (as well as many differences). They are both object-oriented languages much influenced by C++. But while C# is suitable for application development in the Microsoft ecosystem from the front, Java is considered best for client-side web applications. Also, while C# has many tools for programming, Java has a larger arsenal of tools to choose from in IDEs and Text Editors. C# is used for virtual reality projects like games, mobile, and web applications. It is built specifically for Microsoft platforms and several non-Microsoft-based operating systems, like the Mono Project that works with Linux and OS X. Java is used for creating messaging applications and developing web-based and enterprise-based applications in open-source ecosystems. Both C# and Java support arrays. However, each language uses them differently. In C#, arrays are a specialization of the system; in Java, they are a direct specialization of the object. The C# programming language executes on the CLR. The source code is interpreted into bytecode, which is further compiled by the CLR. Java runs on any platform with the assistance of JRE (Java Runtime Environment). The written source code is first compiled into bytecode and then converted into machine code to be executed on a JRE. C# and C++ Although C# and C++ are both C-based languages with similar code, there are some differences. For one, C# is considered a component-oriented programming language, while C++ is a partial object-oriented language. Also, while both languages are compiled languages, C# compiles to CLR and is interpreted by.NET, but C++ compiles to machine code. The size of binaries in C# is much larger than in C++. Other differences between the two include the following: C# gives compiler errors and warnings, but C++ doesn’t support warnings, which may cause damage to the OS. C# runs in a virtual machine for automatic memory management. C++ requires you to manage memory manually. C# can create Windows, .NET, web, desktop, and mobile applications, but not stand-alone apps. C++ can create server-side, stand-alone, and console applications as it can work directly with the hardware. C++ can be used on any platform, while C# is targeted toward Windows OS. Generally, C++ being faster than C#, the former is preferred for applications where performance is essential. Features of C# The C# programming language has many features that make it more useful and unique when compared to other languages, including: Object-oriented language Being object-oriented, C# allows the creation of modular applications and reusable codes, an advantage over C++. As an object-oriented language, C# makes development and maintenance easier when project size grows. It supports all three object-oriented features: data encapsulation, inheritance, interfaces, and polymorphism. Simplicity C# is a simple language with a structured approach to problem-solving. Unsafe operations, like direct memory manipulation, are not allowed. Speed The compilation and execution time in C# is very powerful and fast. A Modern programming language C# programming is used for building scalable and interoperable applications with support for modern features like automatic garbage collection, error handling, debugging, and robust security. It has built-in support for a web service to be invoked from any app running on any platform. Type-safe Arrays and objects are zero base indexed and bound checked. There is an automatic checking of the overflow of types. The C# type safety instances support robust programming. Interoperability Language interoperability of C# maximizes code reuse for the efficiency of the development process. C# programs can work upon almost anything as a program can call out any native API. Consistency Its unified type system enables developers to extend the type system simply and easily for consistent behavior. Updateable C# is automatically updateable. Its versioning support enables complex frameworks to be developed and evolved. Component oriented C# supports component-oriented programming through the concepts of properties, methods, events, and attributes for self-contained and self-describing components of functionality for robust and scalable applications. Structured Programming Language The structured design and modularization in C# break a problem into parts, using functions for easy implementation to solve significant problems. Rich Library C# has a standard library with many inbuilt functions for easy and fast development. Prerequisites for Learning C# Basic knowledge of C or C++ or any programming language or programming fundamentals. Additionally, the OOP concept makes for a short learning curve of C#. Advantages of C# There are many advantages to the C# language that makes it a useful programming language compared to other languages like Java, C, or C++. These include: Being an object-oriented language, C# allows you to create modular, maintainable applications and reusable codes Familiar syntax Easy to develop as it has a rich class of libraries for smooth implementation of functions Enhanced integration as an application written in .NET will integrate and interpret better when compared to other NET technologies As C# runs on CLR, it makes it easy to integrate with components written in other languages It’s safe, with no data loss as there is no type-conversion so that you can write secure codes The automatic garbage collection keeps the system clean and doesn’t hang it during execution As your machine has to install the .NET Framework to run C#, it supports cross-platform Strong memory backup prevents memory leakage Programming support of the Microsoft ecosystem makes development easy and seamless Low maintenance cost, as C# can develop iOS, Android, and Windows Phone native apps The syntax is similar to C, C++, and Java, which makes it easier to learn and work with C# Useful as it can develop iOS, Android, and Windows Phone native apps with the Xamarin Framework C# is the most powerful programming language for the .NET Framework Fast development as C# is open source steered by Microsoft with access to open source projects and tools on Github, and many active communities contributing to the improvement What Can C Sharp Do for You? C# can be used to develop a wide range of: Windows client applications Windows libraries and components Windows services Web applications Native iOS and Android mobile apps Azure cloud applications and services Gaming consoles and gaming systems Video and virtual reality games Interoperability software like SharePoint Enterprise software Backend services and database programs AI and ML applications Distributed applications Hardware-level programming Virus and malware software GUI-based applications IoT devices Blockchain and distributed ledger technology C# Programming for Beginners: Introduction, Features and Applications By Simplilearn Last updated on Jan 20, 2020674 C# Programming for Beginners As a programmer, you’re motivated to master the most popular languages that will give you an edge in your career. There’s a vast number of programming languages that you can learn, but how do you know which is the most useful? If you know C and C++, do you need to learn C# as well? How similar is C# to Java? Does it become more comfortable for you to learn C# if you already know Java? Every developer and wannabe programmer asks these types of questions. So let us explore C# programming: how it evolved as an extension of C and why you need to learn it as a part of the Master’s Program in integrated DevOps for server-side execution. Are you a web developer or someone interested to build a website? Enroll for the Javascript Certification Training. Check out the course preview now! What is C#? C# is a modern object-oriented programming language developed in 2000 by Anders Hejlsberg, the principal designer and lead architect at Microsoft. It is pronounced as "C-Sharp," inspired by the musical notation “♯” which stands for a note with a slightly higher pitch. As it’s considered an incremental compilation of the C++ language, the name C “sharp” seemed most appropriate. The sharp symbol, however, has been replaced by the keyboard friendly “#” as a suffix to “C” for purposes of programming. Although the code is very similar to C++, C# is newer and has grown fast with extensive support from Microsoft. The fact that it’s so similar to Java syntactically helps explain why it has emerged as one of the most popular programming languages today. An Introduction to C# Programming C# is a general-purpose, object-oriented programming language that is structured and easy to learn. It runs on Microsoft’s .Net Framework and can be compiled on a variety of computer platforms. As the syntax is simple and easy to learn, developers familiar with C, C++, or Java have found a comfort zone within C#. C# is a boon for developers who want to build a wide range of applications on the .NET Framework—Windows applications, Web applications, and Web services—in addition to building mobile apps, Windows Store apps, and enterprise software. It is thus considered a powerful programming language and features in every developer’s cache of tools. Although first released in 2002, when it was introduced with .NET Framework 1.0, the C# language has evolved a great deal since then. The most recent version is C# 8.0, available in preview as part of Visual Studio. To get access to all of the new language features, you would need to install the latest preview version of .NET Core 3.0. The C# Environment You need the .NET Framework and an IDE (integrated development environment) to work with the C# language. The .NET Framework The .NET Framework platform of the Windows OS is required to write web and desktop-based applications using not only C# but also Visual Basic and Jscript, as the platform provides language interoperability. Besides, the .Net Framework allows C# to communicate with any of the other common languages, such as C++, Jscript, COBOL, and so on. IDEs Microsoft provides various IDEs for C# programming: Visual Studio 2010 (VS) Visual Studio Express Visual Web Developer Visual Studio Code (VSC) The C# source code files can be written using a basic text editor, like Notepad, and compiled using the command-line compiler of the .NET Framework. Alternative open-source versions of the .Net Framework can work on other operating systems as well. For instance, the Mono has a C# compiler and runs on several operating systems, including Linux, Mac, Android, BSD, iOS, Windows, Solaris, and UNIX. This brings enhanced development tools to the developer. As C# is part of the .Net Framework platform, it has access to its enormous library of codes and components, such as Common Language Runtime (CLR), the .Net Framework Class Library, Common Language Specification, Common Type System, Metadata and Assemblies, Windows Forms, ASP.Net and ASP.Net AJAX, Windows Workflow Foundation (WF), Windows Communication Foundation (WCF), and LINQ. C# and Java C# and Java are high-level programming languages that share several similarities (as well as many differences). They are both object-oriented languages much influenced by C++. But while C# is suitable for application development in the Microsoft ecosystem from the front, Java is considered best for client-side web applications. Also, while C# has many tools for programming, Java has a larger arsenal of tools to choose from in IDEs and Text Editors. C# is used for virtual reality projects like games, mobile, and web applications. It is built specifically for Microsoft platforms and several non-Microsoft-based operating systems, like the Mono Project that works with Linux and OS X. Java is used for creating messaging applications and developing web-based and enterprise-based applications in open-source ecosystems. Both C# and Java support arrays. However, each language uses them differently. In C#, arrays are a specialization of the system; in Java, they are a direct specialization of the object. The C# programming language executes on the CLR. The source code is interpreted into bytecode, which is further compiled by the CLR. Java runs on any platform with the assistance of JRE (Java Runtime Environment). The written source code is first compiled into bytecode and then converted into machine code to be executed on a JRE. C# and C++ Although C# and C++ are both C-based languages with similar code, there are some differences. For one, C# is considered a component-oriented programming language, while C++ is a partial object-oriented language. Also, while both languages are compiled languages, C# compiles to CLR and is interpreted by.NET, but C++ compiles to machine code. The size of binaries in C# is much larger than in C++. Other differences between the two include the following: C# gives compiler errors and warnings, but C++ doesn’t support warnings, which may cause damage to the OS. C# runs in a virtual machine for automatic memory management. C++ requires you to manage memory manually. C# can create Windows, .NET, web, desktop, and mobile applications, but not stand-alone apps. C++ can create server-side, stand-alone, and console applications as it can work directly with the hardware. C++ can be used on any platform, while C# is targeted toward Windows OS. Generally, C++ being faster than C#, the former is preferred for applications where performance is essential. Features of C# The C# programming language has many features that make it more useful and unique when compared to other languages, including: Object-oriented language Being object-oriented, C# allows the creation of modular applications and reusable codes, an advantage over C++. As an object-oriented language, C# makes development and maintenance easier when project size grows. It supports all three object-oriented features: data encapsulation, inheritance, interfaces, and polymorphism. Simplicity C# is a simple language with a structured approach to problem-solving. Unsafe operations, like direct memory manipulation, are not allowed. Speed The compilation and execution time in C# is very powerful and fast. A Modern programming language C# programming is used for building scalable and interoperable applications with support for modern features like automatic garbage collection, error handling, debugging, and robust security. It has built-in support for a web service to be invoked from any app running on any platform. Type-safe Arrays and objects are zero base indexed and bound checked. There is an automatic checking of the overflow of types. The C# type safety instances support robust programming. Interoperability Language interoperability of C# maximizes code reuse for the efficiency of the development process. C# programs can work upon almost anything as a program can call out any native API. Consistency Its unified type system enables developers to extend the type system simply and easily for consistent behavior. Updateable C# is automatically updateable. Its versioning support enables complex frameworks to be developed and evolved. Component oriented C# supports component-oriented programming through the concepts of properties, methods, events, and attributes for self-contained and self-describing components of functionality for robust and scalable applications. Structured Programming Language The structured design and modularization in C# break a problem into parts, using functions for easy implementation to solve significant problems. Rich Library C# has a standard library with many inbuilt functions for easy and fast development. Full Stack Java Developer Course The Gateway to Master Web DevelopmentEXPLORE COURSEFull Stack Java Developer Course Prerequisites for Learning C# Basic knowledge of C or C++ or any programming language or programming fundamentals. Additionally, the OOP concept makes for a short learning curve of C#. Advantages of C# There are many advantages to the C# language that makes it a useful programming language compared to other languages like Java, C, or C++. These include: Being an object-oriented language, C# allows you to create modular, maintainable applications and reusable codes Familiar syntax Easy to develop as it has a rich class of libraries for smooth implementation of functions Enhanced integration as an application written in .NET will integrate and interpret better when compared to other NET technologies As C# runs on CLR, it makes it easy to integrate with components written in other languages It’s safe, with no data loss as there is no type-conversion so that you can write secure codes The automatic garbage collection keeps the system clean and doesn’t hang it during execution As your machine has to install the .NET Framework to run C#, it supports cross-platform Strong memory backup prevents memory leakage Programming support of the Microsoft ecosystem makes development easy and seamless Low maintenance cost, as C# can develop iOS, Android, and Windows Phone native apps The syntax is similar to C, C++, and Java, which makes it easier to learn and work with C# Useful as it can develop iOS, Android, and Windows Phone native apps with the Xamarin Framework C# is the most powerful programming language for the .NET Framework Fast development as C# is open source steered by Microsoft with access to open source projects and tools on Github, and many active communities contributing to the improvement What Can C Sharp Do for You? C# can be used to develop a wide range of: Windows client applications Windows libraries and components Windows services Web applications Native iOS and Android mobile apps Azure cloud applications and services Gaming consoles and gaming systems Video and virtual reality games Interoperability software like SharePoint Enterprise software Backend services and database programs AI and ML applications Distributed applications Hardware-level programming Virus and malware software GUI-based applications IoT devices Blockchain and distributed ledger technology Who Should Learn the C# Programming Language and Why? C# is one of the most popular programming languages as it can be used for a variety of applications: mobile apps, game development, and enterprise software. What’s more, the C# 8.0 version is packed with several new features and enhancements to the C# language that can change the way developers write their C# code. The most important new features available are ‘null reference types,’ enhanced ‘pattern matching,’ and ‘async streams’ that help you to write more reliable and readable code. As you’re exposed to the fundamental programming concepts of C# in this course, you can work on projects that open the doors for you as a Full Stack Java Developer. So, upskill and master the C# language for a faster career trajectory and salary scope.
Ulrich-Tonmoy / Cheat SheetsCheat Sheets heaven for all kind of programming language and frameworks + Game and Web dev + AI.
nanshaws / LibgdxTutoriallibgdx 教程项目 本项目旨在提供完整的libgdx桌面教程，帮助开发者快速掌握libgdx游戏开发框架的使用。成功的将gdx-ai和ashley的tests从官网剥离出来,并成功运行。libgdx tutorial project This project aims to provide a complete libgdx desktop tutorial to help developers quickly master the use of libgdx game development framework. Successfully separated GDX-AI and Ashley's tests from the official website and ran them
Aryia-Behroziuan / ReferencesPoole, Mackworth & Goebel 1998, p. 1. Russell & Norvig 2003, p. 55. Definition of AI as the study of intelligent agents: Poole, Mackworth & Goebel (1998), which provides the version that is used in this article. These authors use the term "computational intelligence" as a synonym for artificial intelligence.[1] Russell & Norvig (2003) (who prefer the term "rational agent") and write "The whole-agent view is now widely accepted in the field".[2] Nilsson 1998 Legg & Hutter 2007 Russell & Norvig 2009, p. 2. McCorduck 2004, p. 204 Maloof, Mark. "Artificial Intelligence: An Introduction, p. 37" (PDF). georgetown.edu. Archived (PDF) from the original on 25 August 2018. "How AI Is Getting Groundbreaking Changes In Talent Management And HR Tech". Hackernoon. Archived from the original on 11 September 2019. Retrieved 14 February 2020. Schank, Roger C. (1991). "Where's the AI". AI magazine. Vol. 12 no. 4. p. 38. Russell & Norvig 2009. "AlphaGo – Google DeepMind". Archived from the original on 10 March 2016. Allen, Gregory (April 2020). "Department of Defense Joint AI Center - Understanding AI Technology" (PDF). AI.mil - The official site of the Department of Defense Joint Artificial Intelligence Center. Archived (PDF) from the original on 21 April 2020. Retrieved 25 April 2020. Optimism of early AI: * Herbert Simon quote: Simon 1965, p. 96 quoted in Crevier 1993, p. 109. * Marvin Minsky quote: Minsky 1967, p. 2 quoted in Crevier 1993, p. 109. Boom of the 1980s: rise of expert systems, Fifth Generation Project, Alvey, MCC, SCI: * McCorduck 2004, pp. 426–441 * Crevier 1993, pp. 161–162,197–203, 211, 240 * Russell & Norvig 2003, p. 24 * NRC 1999, pp. 210–211 * Newquist 1994, pp. 235–248 First AI Winter, Mansfield Amendment, Lighthill report * Crevier 1993, pp. 115–117 * Russell & Norvig 2003, p. 22 * NRC 1999, pp. 212–213 * Howe 1994 * Newquist 1994, pp. 189–201 Second AI winter: * McCorduck 2004, pp. 430–435 * Crevier 1993, pp. 209–210 * NRC 1999, pp. 214–216 * Newquist 1994, pp. 301–318 AI becomes hugely successful in the early 21st century * Clark 2015 Pamela McCorduck (2004, p. 424) writes of "the rough shattering of AI in subfields—vision, natural language, decision theory, genetic algorithms, robotics ... and these with own sub-subfield—that would hardly have anything to say to each other." This list of intelligent traits is based on the topics covered by the major AI textbooks, including: * Russell & Norvig 2003 * Luger & Stubblefield 2004 * Poole, Mackworth & Goebel 1998 * Nilsson 1998 Kolata 1982. Maker 2006. Biological intelligence vs. intelligence in general: Russell & Norvig 2003, pp. 2–3, who make the analogy with aeronautical engineering. McCorduck 2004, pp. 100–101, who writes that there are "two major branches of artificial intelligence: one aimed at producing intelligent behavior regardless of how it was accomplished, and the other aimed at modeling intelligent processes found in nature, particularly human ones." Kolata 1982, a paper in Science, which describes McCarthy's indifference to biological models. Kolata quotes McCarthy as writing: "This is AI, so we don't care if it's psychologically real".[19] McCarthy recently reiterated his position at the AI@50 conference where he said "Artificial intelligence is not, by definition, simulation of human intelligence".[20]. Neats vs. scruffies: * McCorduck 2004, pp. 421–424, 486–489 * Crevier 1993, p. 168 * Nilsson 1983, pp. 10–11 Symbolic vs. sub-symbolic AI: * Nilsson (1998, p. 7), who uses the term "sub-symbolic". General intelligence (strong AI) is discussed in popular introductions to AI: * Kurzweil 1999 and Kurzweil 2005 See the Dartmouth proposal, under Philosophy, below. McCorduck 2004, p. 34. McCorduck 2004, p. xviii. McCorduck 2004, p. 3. McCorduck 2004, pp. 340–400. This is a central idea of Pamela McCorduck's Machines Who Think. She writes: "I like to think of artificial intelligence as the scientific apotheosis of a venerable cultural tradition."[26] "Artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized."[27] "Our history is full of attempts—nutty, eerie, comical, earnest, legendary and real—to make artificial intelligences, to reproduce what is the essential us—bypassing the ordinary means. Back and forth between myth and reality, our imaginations supplying what our workshops couldn't, we have engaged for a long time in this odd form of self-reproduction."[28] She traces the desire back to its Hellenistic roots and calls it the urge to "forge the Gods."[29] "Stephen Hawking believes AI could be mankind's last accomplishment". BetaNews. 21 October 2016. Archived from the original on 28 August 2017. Lombardo P, Boehm I, Nairz K (2020). "RadioComics – Santa Claus and the future of radiology". Eur J Radiol. 122 (1): 108771. doi:10.1016/j.ejrad.2019.108771. PMID 31835078. Ford, Martin; Colvin, Geoff (6 September 2015). "Will robots create more jobs than they destroy?". The Guardian. Archived from the original on 16 June 2018. Retrieved 13 January 2018. AI applications widely used behind the scenes: * Russell & Norvig 2003, p. 28 * Kurzweil 2005, p. 265 * NRC 1999, pp. 216–222 * Newquist 1994, pp. 189–201 AI in myth: * McCorduck 2004, pp. 4–5 * Russell & Norvig 2003, p. 939 AI in early science fiction. * McCorduck 2004, pp. 17–25 Formal reasoning: * Berlinski, David (2000). The Advent of the Algorithm. Harcourt Books. ISBN 978-0-15-601391-8. OCLC 46890682. Archived from the original on 26 July 2020. Retrieved 22 August 2020. Turing, Alan (1948), "Machine Intelligence", in Copeland, B. Jack (ed.), The Essential Turing: The ideas that gave birth to the computer age, Oxford: Oxford University Press, p. 412, ISBN 978-0-19-825080-7 Russell & Norvig 2009, p. 16. Dartmouth conference: * McCorduck 2004, pp. 111–136 * Crevier 1993, pp. 47–49, who writes "the conference is generally recognized as the official birthdate of the new science." * Russell & Norvig 2003, p. 17, who call the conference "the birth of artificial intelligence." * NRC 1999, pp. 200–201 McCarthy, John (1988). "Review of The Question of Artificial Intelligence". Annals of the History of Computing. 10 (3): 224–229., collected in McCarthy, John (1996). "10. Review of The Question of Artificial Intelligence". Defending AI Research: A Collection of Essays and Reviews. CSLI., p. 73, "[O]ne of the reasons for inventing the term "artificial intelligence" was to escape association with "cybernetics". Its concentration on analog feedback seemed misguided, and I wished to avoid having either to accept Norbert (not Robert) Wiener as a guru or having to argue with him." Hegemony of the Dartmouth conference attendees: * Russell & Norvig 2003, p. 17, who write "for the next 20 years the field would be dominated by these people and their students." * McCorduck 2004, pp. 129–130 Russell & Norvig 2003, p. 18. Schaeffer J. (2009) Didn't Samuel Solve That Game?. In: One Jump Ahead. Springer, Boston, MA Samuel, A. L. (July 1959). "Some Studies in Machine Learning Using the Game of Checkers". IBM Journal of Research and Development. 3 (3): 210–229. CiteSeerX 10.1.1.368.2254. doi:10.1147/rd.33.0210. "Golden years" of AI (successful symbolic reasoning programs 1956–1973): * McCorduck 2004, pp. 243–252 * Crevier 1993, pp. 52–107 * Moravec 1988, p. 9 * Russell & Norvig 2003, pp. 18–21 The programs described are Arthur Samuel's checkers program for the IBM 701, Daniel Bobrow's STUDENT, Newell and Simon's Logic Theorist and Terry Winograd's SHRDLU. DARPA pours money into undirected pure research into AI during the 1960s: * McCorduck 2004, p. 131 * Crevier 1993, pp. 51, 64–65 * NRC 1999, pp. 204–205 AI in England: * Howe 1994 Lighthill 1973. Expert systems: * ACM 1998, I.2.1 * Russell & Norvig 2003, pp. 22–24 * Luger & Stubblefield 2004, pp. 227–331 * Nilsson 1998, chpt. 17.4 * McCorduck 2004, pp. 327–335, 434–435 * Crevier 1993, pp. 145–62, 197–203 * Newquist 1994, pp. 155–183 Mead, Carver A.; Ismail, Mohammed (8 May 1989). Analog VLSI Implementation of Neural Systems (PDF). The Kluwer International Series in Engineering and Computer Science. 80. Norwell, MA: Kluwer Academic Publishers. doi:10.1007/978-1-4613-1639-8. ISBN 978-1-4613-1639-8. Archived from the original (PDF) on 6 November 2019. Retrieved 24 January 2020. Formal methods are now preferred ("Victory of the neats"): * Russell & Norvig 2003, pp. 25–26 * McCorduck 2004, pp. 486–487 McCorduck 2004, pp. 480–483. Markoff 2011. 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Cognitive Systems Research. 48: 39–55. doi:10.1016/j.cogsys.2017.05.001. hdl:2318/1665207. S2CID 206868967. Problem solving, puzzle solving, game playing and deduction: * Russell & Norvig 2003, chpt. 3–9, * Poole, Mackworth & Goebel 1998, chpt. 2,3,7,9, * Luger & Stubblefield 2004, chpt. 3,4,6,8, * Nilsson 1998, chpt. 7–12 Uncertain reasoning: * Russell & Norvig 2003, pp. 452–644, * Poole, Mackworth & Goebel 1998, pp. 345–395, * Luger & Stubblefield 2004, pp. 333–381, * Nilsson 1998, chpt. 19 Psychological evidence of sub-symbolic reasoning: * Wason & Shapiro (1966) showed that people do poorly on completely abstract problems, but if the problem is restated to allow the use of intuitive social intelligence, performance dramatically improves. (See Wason selection task) * Kahneman, Slovic & Tversky (1982) have shown that people are terrible at elementary problems that involve uncertain reasoning. (See list of cognitive biases for several examples). * Lakoff & Núñez (2000) have controversially argued that even our skills at mathematics depend on knowledge and skills that come from "the body", i.e. sensorimotor and perceptual skills. (See Where Mathematics Comes From) Knowledge representation: * ACM 1998, I.2.4, * Russell & Norvig 2003, pp. 320–363, * Poole, Mackworth & Goebel 1998, pp. 23–46, 69–81, 169–196, 235–277, 281–298, 319–345, * Luger & Stubblefield 2004, pp. 227–243, * Nilsson 1998, chpt. 18 Knowledge engineering: * Russell & Norvig 2003, pp. 260–266, * Poole, Mackworth & Goebel 1998, pp. 199–233, * Nilsson 1998, chpt. ≈17.1–17.4 Representing categories and relations: Semantic networks, description logics, inheritance (including frames and scripts): * Russell & Norvig 2003, pp. 349–354, * Poole, Mackworth & Goebel 1998, pp. 174–177, * Luger & Stubblefield 2004, pp. 248–258, * Nilsson 1998, chpt. 18.3 Representing events and time:Situation calculus, event calculus, fluent calculus (including solving the frame problem): * Russell & Norvig 2003, pp. 328–341, * Poole, Mackworth & Goebel 1998, pp. 281–298, * Nilsson 1998, chpt. 18.2 Causal calculus: * Poole, Mackworth & Goebel 1998, pp. 335–337 Representing knowledge about knowledge: Belief calculus, modal logics: * Russell & Norvig 2003, pp. 341–344, * Poole, Mackworth & Goebel 1998, pp. 275–277 Sikos, Leslie F. (June 2017). Description Logics in Multimedia Reasoning. Cham: Springer. doi:10.1007/978-3-319-54066-5. ISBN 978-3-319-54066-5. S2CID 3180114. Archived from the original on 29 August 2017. Ontology: * Russell & Norvig 2003, pp. 320–328 Smoliar, Stephen W.; Zhang, HongJiang (1994). "Content based video indexing and retrieval". IEEE Multimedia. 1 (2): 62–72. doi:10.1109/93.311653. S2CID 32710913. Neumann, Bernd; Möller, Ralf (January 2008). "On scene interpretation with description logics". Image and Vision Computing. 26 (1): 82–101. doi:10.1016/j.imavis.2007.08.013. Kuperman, G. J.; Reichley, R. M.; Bailey, T. C. (1 July 2006). "Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations". Journal of the American Medical Informatics Association. 13 (4): 369–371. doi:10.1197/jamia.M2055. PMC 1513681. PMID 16622160. MCGARRY, KEN (1 December 2005). "A survey of interestingness measures for knowledge discovery". The Knowledge Engineering Review. 20 (1): 39–61. doi:10.1017/S0269888905000408. S2CID 14987656. Bertini, M; Del Bimbo, A; Torniai, C (2006). "Automatic annotation and semantic retrieval of video sequences using multimedia ontologies". MM '06 Proceedings of the 14th ACM international conference on Multimedia. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682. Qualification problem: * McCarthy & Hayes 1969 * Russell & Norvig 2003[page needed] While McCarthy was primarily concerned with issues in the logical representation of actions, Russell & Norvig 2003 apply the term to the more general issue of default reasoning in the vast network of assumptions underlying all our commonsense knowledge. Default reasoning and default logic, non-monotonic logics, circumscription, closed world assumption, abduction (Poole et al. places abduction under "default reasoning". Luger et al. places this under "uncertain reasoning"): * Russell & Norvig 2003, pp. 354–360, * Poole, Mackworth & Goebel 1998, pp. 248–256, 323–335, * Luger & Stubblefield 2004, pp. 335–363, * Nilsson 1998, ~18.3.3 Breadth of commonsense knowledge: * Russell & Norvig 2003, p. 21, * Crevier 1993, pp. 113–114, * Moravec 1988, p. 13, * Lenat & Guha 1989 (Introduction) Dreyfus & Dreyfus 1986. Gladwell 2005. Expert knowledge as embodied intuition: * Dreyfus & Dreyfus 1986 (Hubert Dreyfus is a philosopher and critic of AI who was among the first to argue that most useful human knowledge was encoded sub-symbolically. See Dreyfus' critique of AI) * Gladwell 2005 (Gladwell's Blink is a popular introduction to sub-symbolic reasoning and knowledge.) * Hawkins & Blakeslee 2005 (Hawkins argues that sub-symbolic knowledge should be the primary focus of AI research.) Planning: * ACM 1998, ~I.2.8, * Russell & Norvig 2003, pp. 375–459, * Poole, Mackworth & Goebel 1998, pp. 281–316, * Luger & Stubblefield 2004, pp. 314–329, * Nilsson 1998, chpt. 10.1–2, 22 Information value theory: * Russell & Norvig 2003, pp. 600–604 Classical planning: * Russell & Norvig 2003, pp. 375–430, * Poole, Mackworth & Goebel 1998, pp. 281–315, * Luger & Stubblefield 2004, pp. 314–329, * Nilsson 1998, chpt. 10.1–2, 22 Planning and acting in non-deterministic domains: conditional planning, execution monitoring, replanning and continuous planning: * Russell & Norvig 2003, pp. 430–449 Multi-agent planning and emergent behavior: * Russell & Norvig 2003, pp. 449–455 Turing 1950. Solomonoff 1956. Alan Turing discussed the centrality of learning as early as 1950, in his classic paper "Computing Machinery and Intelligence".[120] In 1956, at the original Dartmouth AI summer conference, Ray Solomonoff wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".[121] This is a form of Tom Mitchell's widely quoted definition of machine learning: "A computer program is set to learn from an experience E with respect to some task T and some performance measure P if its performance on T as measured by P improves with experience E." Learning: * ACM 1998, I.2.6, * Russell & Norvig 2003, pp. 649–788, * Poole, Mackworth & Goebel 1998, pp. 397–438, * Luger & Stubblefield 2004, pp. 385–542, * Nilsson 1998, chpt. 3.3, 10.3, 17.5, 20 Jordan, M. I.; Mitchell, T. M. (16 July 2015). "Machine learning: Trends, perspectives, and prospects". Science. 349 (6245): 255–260. Bibcode:2015Sci...349..255J. doi:10.1126/science.aaa8415. PMID 26185243. S2CID 677218. Reinforcement learning: * Russell & Norvig 2003, pp. 763–788 * Luger & Stubblefield 2004, pp. 442–449 Natural language processing: * ACM 1998, I.2.7 * Russell & Norvig 2003, pp. 790–831 * Poole, Mackworth & Goebel 1998, pp. 91–104 * Luger & Stubblefield 2004, pp. 591–632 "Versatile question answering systems: seeing in synthesis" Archived 1 February 2016 at the Wayback Machine, Mittal et al., IJIIDS, 5(2), 119–142, 2011 Applications of natural language processing, including information retrieval (i.e. text mining) and machine translation: * Russell & Norvig 2003, pp. 840–857, * Luger & Stubblefield 2004, pp. 623–630 Cambria, Erik; White, Bebo (May 2014). "Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]". IEEE Computational Intelligence Magazine. 9 (2): 48–57. doi:10.1109/MCI.2014.2307227. S2CID 206451986. Vincent, James (7 November 2019). "OpenAI has published the text-generating AI it said was too dangerous to share". The Verge. Archived from the original on 11 June 2020. Retrieved 11 June 2020. Machine perception: * Russell & Norvig 2003, pp. 537–581, 863–898 * Nilsson 1998, ~chpt. 6 Speech recognition: * ACM 1998, ~I.2.7 * Russell & Norvig 2003, pp. 568–578 Object recognition: * Russell & Norvig 2003, pp. 885–892 Computer vision: * ACM 1998, I.2.10 * Russell & Norvig 2003, pp. 863–898 * Nilsson 1998, chpt. 6 Robotics: * ACM 1998, I.2.9, * Russell & Norvig 2003, pp. 901–942, * Poole, Mackworth & Goebel 1998, pp. 443–460 Moving and configuration space: * Russell & Norvig 2003, pp. 916–932 Tecuci 2012. Robotic mapping (localization, etc): * Russell & Norvig 2003, pp. 908–915 Cadena, Cesar; Carlone, Luca; Carrillo, Henry; Latif, Yasir; Scaramuzza, Davide; Neira, Jose; Reid, Ian; Leonard, John J. (December 2016). "Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age". IEEE Transactions on Robotics. 32 (6): 1309–1332. arXiv:1606.05830. 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Retrieved 26 April 2018. Domingos 2015. Artificial brain arguments: AI requires a simulation of the operation of the human brain * Russell & Norvig 2003, p. 957 * Crevier 1993, pp. 271 and 279 A few of the people who make some form of the argument: * Moravec 1988 * Kurzweil 2005, p. 262 * Hawkins & Blakeslee 2005 The most extreme form of this argument (the brain replacement scenario) was put forward by Clark Glymour in the mid-1970s and was touched on by Zenon Pylyshyn and John Searle in 1980. Goertzel, Ben; Lian, Ruiting; Arel, Itamar; de Garis, Hugo; Chen, Shuo (December 2010). "A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures". Neurocomputing. 74 (1–3): 30–49. doi:10.1016/j.neucom.2010.08.012. Nilsson 1983, p. 10. Nils Nilsson writes: "Simply put, there is wide disagreement in the field about what AI is all about."[163] AI's immediate precursors: * McCorduck 2004, pp. 51–107 * Crevier 1993, pp. 27–32 * Russell & Norvig 2003, pp. 15, 940 * Moravec 1988, p. 3 Haugeland 1985, pp. 112–117 The most dramatic case of sub-symbolic AI being pushed into the background was the devastating critique of perceptrons by Marvin Minsky and Seymour Papert in 1969. See History of AI, AI winter, or Frank Rosenblatt. Cognitive simulation, Newell and Simon, AI at CMU (then called Carnegie Tech): * McCorduck 2004, pp. 139–179, 245–250, 322–323 (EPAM) * Crevier 1993, pp. 145–149 Soar (history): * McCorduck 2004, pp. 450–451 * Crevier 1993, pp. 258–263 McCarthy and AI research at SAIL and SRI International: * McCorduck 2004, pp. 251–259 * Crevier 1993 AI research at Edinburgh and in France, birth of Prolog: * Crevier 1993, pp. 193–196 * Howe 1994 AI at MIT under Marvin Minsky in the 1960s : * McCorduck 2004, pp. 259–305 * Crevier 1993, pp. 83–102, 163–176 * Russell & Norvig 2003, p. 19 Cyc: * McCorduck 2004, p. 489, who calls it "a determinedly scruffy enterprise" * Crevier 1993, pp. 239–243 * Russell & Norvig 2003, p. 363−365 * Lenat & Guha 1989 Knowledge revolution: * McCorduck 2004, pp. 266–276, 298–300, 314, 421 * Russell & Norvig 2003, pp. 22–23 Frederick, Hayes-Roth; William, Murray; Leonard, Adelman. "Expert systems". AccessScience. doi:10.1036/1097-8542.248550. Embodied approaches to AI: * McCorduck 2004, pp. 454–462 * Brooks 1990 * Moravec 1988 Weng et al. 2001. Lungarella et al. 2003. Asada et al. 2009. Oudeyer 2010. Revival of connectionism: * Crevier 1993, pp. 214–215 * Russell & Norvig 2003, p. 25 Computational intelligence * IEEE Computational Intelligence Society Archived 9 May 2008 at the Wayback Machine Hutson, Matthew (16 February 2018). "Artificial intelligence faces reproducibility crisis". Science. pp. 725–726. Bibcode:2018Sci...359..725H. doi:10.1126/science.359.6377.725. Archived from the original on 29 April 2018. Retrieved 28 April 2018. Norvig 2012. Langley 2011. Katz 2012. The intelligent agent paradigm: * Russell & Norvig 2003, pp. 27, 32–58, 968–972 * Poole, Mackworth & Goebel 1998, pp. 7–21 * Luger & Stubblefield 2004, pp. 235–240 * Hutter 2005, pp. 125–126 The definition used in this article, in terms of goals, actions, perception and environment, is due to Russell & Norvig (2003). Other definitions also include knowledge and learning as additional criteria. Agent architectures, hybrid intelligent systems: * Russell & Norvig (2003, pp. 27, 932, 970–972) * Nilsson (1998, chpt. 25) Hierarchical control system: * Albus 2002 Lieto, Antonio; Lebiere, Christian; Oltramari, Alessandro (May 2018). "The knowledge level in cognitive architectures: Current limitations and possibile developments". Cognitive Systems Research. 48: 39–55. doi:10.1016/j.cogsys.2017.05.001. hdl:2318/1665207. S2CID 206868967. Lieto, Antonio; Bhatt, Mehul; Oltramari, Alessandro; Vernon, David (May 2018). "The role of cognitive architectures in general artificial intelligence". Cognitive Systems Research. 48: 1–3. doi:10.1016/j.cogsys.2017.08.003. hdl:2318/1665249. S2CID 36189683. Russell & Norvig 2009, p. 1. White Paper: On Artificial Intelligence - A European approach to excellence and trust (PDF). Brussels: European Commission. 2020. p. 1. Archived (PDF) from the original on 20 February 2020. Retrieved 20 February 2020. CNN 2006. Using AI to predict flight delays Archived 20 November 2018 at the Wayback Machine, Ishti.org. N. Aletras; D. Tsarapatsanis; D. Preotiuc-Pietro; V. Lampos (2016). "Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective". PeerJ Computer Science. 2: e93. doi:10.7717/peerj-cs.93. "The Economist Explains: Why firms are piling into artificial intelligence". The Economist. 31 March 2016. Archived from the original on 8 May 2016. Retrieved 19 May 2016. Lohr, Steve (28 February 2016). "The Promise of Artificial Intelligence Unfolds in Small Steps". The New York Times. Archived from the original on 29 February 2016. Retrieved 29 February 2016. Frangoul, Anmar (14 June 2019). "A Californian business is using A.I. to change the way we think about energy storage". CNBC. Archived from the original on 25 July 2020. Retrieved 5 November 2019. Wakefield, Jane (15 June 2016). "Social media 'outstrips TV' as news source for young people". BBC News. Archived from the original on 24 June 2016. Smith, Mark (22 July 2016). "So you think you chose to read this article?". BBC News. Archived from the original on 25 July 2016. Brown, Eileen. "Half of Americans do not believe deepfake news could target them online". ZDNet. Archived from the original on 6 November 2019. Retrieved 3 December 2019. The Turing test: Turing's original publication: * Turing 1950 Historical influence and philosophical implications: * Haugeland 1985, pp. 6–9 * Crevier 1993, p. 24 * McCorduck 2004, pp. 70–71 * Russell & Norvig 2003, pp. 2–3 and 948 Dartmouth proposal: * McCarthy et al. 1955 (the original proposal) * Crevier 1993, p. 49 (historical significance) The physical symbol systems hypothesis: * Newell & Simon 1976, p. 116 * McCorduck 2004, p. 153 * Russell & Norvig 2003, p. 18 Dreyfus 1992, p. 156. Dreyfus criticized the necessary condition of the physical symbol system hypothesis, which he called the "psychological assumption": "The mind can be viewed as a device operating on bits of information according to formal rules."[206] Dreyfus' critique of artificial intelligence: * Dreyfus 1972, Dreyfus & Dreyfus 1986 * Crevier 1993, pp. 120–132 * McCorduck 2004, pp. 211–239 * Russell & Norvig 2003, pp. 950–952, Gödel 1951: in this lecture, Kurt Gödel uses the incompleteness theorem to arrive at the following disjunction: (a) the human mind is not a consistent finite machine, or (b) there exist Diophantine equations for which it cannot decide whether solutions exist. Gödel finds (b) implausible, and thus seems to have believed the human mind was not equivalent to a finite machine, i.e., its power exceeded that of any finite machine. He recognized that this was only a conjecture, since one could never disprove (b). Yet he considered the disjunctive conclusion to be a "certain fact". The Mathematical Objection: * Russell & Norvig 2003, p. 949 * McCorduck 2004, pp. 448–449 Making the Mathematical Objection: * Lucas 1961 * Penrose 1989 Refuting Mathematical Objection: * Turing 1950 under "(2) The Mathematical Objection" * Hofstadter 1979 Background: * Gödel 1931, Church 1936, Kleene 1935, Turing 1937 Graham Oppy (20 January 2015). "Gödel's Incompleteness Theorems". Stanford Encyclopedia of Philosophy. Archived from the original on 22 April 2016. Retrieved 27 April 2016. These Gödelian anti-mechanist arguments are, however, problematic, and there is wide consensus that they fail. Stuart J. Russell; Peter Norvig (2010). "26.1.2: Philosophical Foundations/Weak AI: Can Machines Act Intelligently?/The mathematical objection". Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, NJ: Prentice Hall. ISBN 978-0-13-604259-4. even if we grant that computers have limitations on what they can prove, there is no evidence that humans are immune from those limitations. Mark Colyvan. An introduction to the philosophy of mathematics. Cambridge University Press, 2012. From 2.2.2, 'Philosophical significance of Gödel's incompleteness results': "The accepted wisdom (with which I concur) is that the Lucas-Penrose arguments fail." Iphofen, Ron; Kritikos, Mihalis (3 January 2019). "Regulating artificial intelligence and robotics: ethics by design in a digital society". Contemporary Social Science: 1–15. doi:10.1080/21582041.2018.1563803. ISSN 2158-2041. "Ethical AI Learns Human Rights Framework". Voice of America. Archived from the original on 11 November 2019. Retrieved 10 November 2019. Crevier 1993, pp. 132–144. In the early 1970s, Kenneth Colby presented a version of Weizenbaum's ELIZA known as DOCTOR which he promoted as a serious therapeutic tool.[216] Joseph Weizenbaum's critique of AI: * Weizenbaum 1976 * Crevier 1993, pp. 132–144 * McCorduck 2004, pp. 356–373 * Russell & Norvig 2003, p. 961 Weizenbaum (the AI researcher who developed the first chatterbot program, ELIZA) argued in 1976 that the misuse of artificial intelligence has the potential to devalue human life. Wendell Wallach (2010). Moral Machines, Oxford University Press. Wallach, pp 37–54. Wallach, pp 55–73. Wallach, Introduction chapter. Michael Anderson and Susan Leigh Anderson (2011), Machine Ethics, Cambridge University Press. "Machine Ethics". aaai.org. Archived from the original on 29 November 2014. Rubin, Charles (Spring 2003). "Artificial Intelligence and Human Nature". The New Atlantis. 1: 88–100. Archived from the original on 11 June 2012. Brooks, Rodney (10 November 2014). "artificial intelligence is a tool, not a threat". Archived from the original on 12 November 2014. "Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence". Observer. 19 August 2015. Archived from the original on 30 October 2015. Retrieved 30 October 2015. Chalmers, David (1995). "Facing up to the problem of consciousness". Journal of Consciousness Studies. 2 (3): 200–219. Archived from the original on 8 March 2005. Retrieved 11 October 2018. See also this link Archived 8 April 2011 at the Wayback Machine Horst, Steven, (2005) "The Computational Theory of Mind" Archived 11 September 2018 at the Wayback Machine in The Stanford Encyclopedia of Philosophy Searle 1980, p. 1. This version is from Searle (1999), and is also quoted in Dennett 1991, p. 435. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." [230] Strong AI is defined similarly by Russell & Norvig (2003, p. 947): "The assertion that machines could possibly act intelligently
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Previous</span></a> <a class="w3-btn" href="default.asp"><span class="w3-hide-small">Complete HTML </span>Reference</a> <a class="w3-right w3-btn" href="tag_param.asp"><span class="w3-hide-small">Next </span>❯</a> </div> <br> <div class="w3-example"> <h3>Example</h3> <p>A paragraph is marked up as follows:</p> <div class="w3-code notranslate htmlHigh"> <span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>p<span class="tagcolor" style="color:mediumblue">></span></span>This is some text in a paragraph.<span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>/p<span class="tagcolor" style="color:mediumblue">></span></span> </div> <a target="_blank" href="tryit.asp?filename=tryhtml_paragraphs1" class="w3-btn w3-margin-bottom">Try it Yourself »</a> </div> <p>More "Try it Yourself" examples below.</p> <hr> <h2>Definition and Usage</h2> <p>The <code class="w3-codespan"><p></code> tag defines a paragraph.</p> <p>Browsers automatically add a single blank line before and after each <code class="w3-codespan"><p></code> element.</p> <p><strong>Tip:</strong> Use CSS to <a href="/html/html_css.asp">style paragraphs</a>.</p> <hr> <h2>Browser Support</h2> <table class="browserref notranslate"> <tbody><tr> <th style="width:20%;font-size:16px;text-align:left;">Element</th> <th style="width:16%;" class="bsChrome" title="Chrome"></th> <th style="width:16%;" class="bsEdge" title="Internet Explorer / Edge"></th> <th style="width:16%;" class="bsFirefox" title="Firefox"></th> <th style="width:16%;" class="bsSafari" title="Safari"></th> <th style="width:16%;" class="bsOpera" title="Opera"></th> </tr><tr> <td style="text-align:left;"><p></td> <td>Yes</td> <td>Yes</td> <td>Yes</td> <td>Yes</td> <td>Yes</td> </tr> </tbody></table> <hr> <h2>Global Attributes</h2> <p>The <code class="w3-codespan"><p></code> tag also supports the <a href="ref_standardattributes.asp">Global Attributes in HTML</a>.</p> <hr> <h2>Event Attributes</h2> <p>The <code class="w3-codespan"><p></code> tag also supports the <a href="ref_eventattributes.asp">Event Attributes in HTML</a>.</p> <hr> <div id="midcontentadcontainer" style="overflow:auto;text-align:center"> <!-- MidContent --> <!-- <p class="adtext">Advertisement</p> --> <div id="adngin-mid_content-0" data-google-query-id="CKfs_8ueqvcCFXiOSwUd2fYBLg"><div id="sn_ad_label_adngin-mid_content-0" class="sn_ad_label" style="color:#000000;font-size:12px;margin:0;text-align:center;">ADVERTISEMENT</div><div id="google_ads_iframe_/22152718,16833175/sws-hb//w3schools.com//mid_content_1__container__" style="border: 0pt none; display: inline-block; width: 300px; height: 250px;"><iframe frameborder="0" src="https://56d0da6c34aaa471db22bb4266aac656.safeframe.googlesyndication.com/safeframe/1-0-38/html/container.html" id="google_ads_iframe_/22152718,16833175/sws-hb//w3schools.com//mid_content_1" title="3rd party ad content" name="" scrolling="no" marginwidth="0" marginheight="0" width="300" height="250" data-is-safeframe="true" sandbox="allow-forms allow-popups allow-popups-to-escape-sandbox allow-same-origin allow-scripts allow-top-navigation-by-user-activation" role="region" aria-label="Advertisement" tabindex="0" data-google-container-id="8" style="border: 0px; vertical-align: bottom;" data-load-complete="true"></iframe></div></div> </div> <hr> <h2>More Examples</h2> <div class="w3-example"> <h3>Example</h3> <p>Align text in a paragraph (with CSS):</p> <div class="w3-code notranslate htmlHigh"> <span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>p<span class="attributecolor" style="color:red"> style<span class="attributevaluecolor" style="color:mediumblue">="text-align:right"</span></span><span class="tagcolor" style="color:mediumblue">></span></span>This is some text in a paragraph.<span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>/p<span class="tagcolor" style="color:mediumblue">></span></span> </div> <a target="_blank" href="tryit.asp?filename=tryhtml_p_align_css" class="w3-btn w3-margin-bottom">Try it Yourself »</a> </div> <div class="w3-example"> <h3>Example</h3> <p>Style paragraphs with CSS:</p> <div class="w3-code notranslate htmlHigh"> <span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>html<span class="tagcolor" style="color:mediumblue">></span></span><br><span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>head<span class="tagcolor" style="color:mediumblue">></span></span><br><span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>style<span class="tagcolor" style="color:mediumblue">></span></span><span class="cssselectorcolor" style="color:brown"><br>p <span class="cssdelimitercolor" style="color:black">{</span><span class="csspropertycolor" style="color:red"><br> color<span class="csspropertyvaluecolor" style="color:mediumblue"><span class="cssdelimitercolor" style="color:black">:</span> navy<span class="cssdelimitercolor" style="color:black">;</span></span><br> text-indent<span class="csspropertyvaluecolor" style="color:mediumblue"><span class="cssdelimitercolor" style="color:black">:</span> 30px<span class="cssdelimitercolor" style="color:black">;</span></span><br> text-transform<span class="csspropertyvaluecolor" style="color:mediumblue"><span class="cssdelimitercolor" style="color:black">:</span> uppercase<span class="cssdelimitercolor" style="color:black">;</span></span><br></span><span class="cssdelimitercolor" style="color:black">}</span><br></span><span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>/style<span class="tagcolor" style="color:mediumblue">></span></span><br> <span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>/head<span class="tagcolor" style="color:mediumblue">></span></span><br><span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>body<span class="tagcolor" style="color:mediumblue">></span></span><br><br><span class="tagnamecolor" style="color:brown"><span class="tagcolor" style="color:mediumblue"><</span>p<span class="tagcolor" style="color:mediumblue">></span></span>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. 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