16 skills found
perks-project / Pk OntologyRepository for the Procedural Knowledge Ontology (PKO)
dongyh20 / Demo ICLDemo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition
danielcamposramos / Knowledge3DWeb knowledge is fragmented — duplicated across fonts, embeddings, metadata, and renderings. Humans see pixels, AI sees tokens, neither shares the source. Knowledge3D: a sovereign GPU-native reference implementation for W3C PM-KR, where humans and AI consume the same procedural knowledge from one source.
Antrophyy / MinecraftUnrealEngineThe Unreal Engine 4 project to try and recreate Minecraft. Done purely in c++. For terrain generation I used procedural mesh. Done to broaden the knowledge of game development and c++.
cefriel / Procedural Kg LlmPrompt-based pipeline for extracting procedural knowledge graphs from text with LLMs
allenai / PlaSmaThis is a repository for paper titled, PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning
aharri64 / Complete Csharp MasterclassHave you ever had an idea for a program, an app, or a game? Maybe you want to work as a developer? Then you are in the right place. In this course, you are going to discover how to become a c# developer - one of the best programming languages on earth! C# is one of the few programming languages which allows you to create amazing cross-platform Mobile Apps, Games, and PC Programs. Bringing an Idea to life is one of the best feelings one can have, but the path to get there is often full of challenges. So I have created a course that makes this path as easy as possible all with the help of c# so that you become a skilled c# developer! You start off by learning the C# basics and C# programming concepts in general: variables methods arrays if statements loops Then you learn the three pillars of Object-oriented programming. Classes and Objects Inheritance Polymorphism Once you mastered them you will go into advanced C# Topics, such as Databases and LINQ. In order to really become really good in c# programming, you have to program yourself, so I have created loads of exercises (and quizzes) for you to try for yourself to do c# programming and also to see how it is done afterward. Of course, you learn best programming practices along the way. Equipped with those skills, you will build beautiful user interfaces with WPF - A framework, which makes creating GUI’s a piece of cake. By that point, you can create your very own complex programs. But what comes next is even cooler. Learn Game Development with Unity and C# - Build 2 awesome games As C# can be used for multiple different areas of programming, I have decided to cover the most important ones. So I have added a whole bunch of chapters specifically designed for a C# developer and Unity game developer - arguably the best Game Engine in the world. In those chapters, you will discover how to create your very own video games by building pong, the mother of video games and zig-zag, an amazing and successful endless runner game. We live in a world, where knowledge and work are shared more than ever, so using assets provided by others is a huge boost to your progress. You will learn how to use 3D assets to make an endless runner. Then you’ll use animations, reset the game, use particle systems, and finally create a map procedurally. That’s quite some advanced stuff right there. I know that learning to code can be hard at times, and sometimes you just get stuck. But no worries, we are there for you. We answer each question as quickly as we can and make sure that you reach your goal of becoming a developer. WHO IS THIS COURSE FOR? The course is for anyone, who wants to learn c# and wants to become professionally good in c# programming. No experience is required whatsoever. It is designed that anyone who can handle a mouse and keyboard will succeed in finishing it. The only real requisite is the desire to learn. 30-DAY FULL MONEY-BACK GUARANTEE This course comes with a 30-day full money-back guarantee. Take the course, watch every lecture, and do the exercises, and if you feel like this course is not for you, ask for a full refund within 30 days. All your money back, no questions asked. ABOUT YOUR INSTRUCTOR: My name is Denis Panjuta and in my courses, I have taught over 150.000 students how to code. I have a Bachelor of Engineering at the University of Applied Sciences in Constance (Germany). I love teaching and creating high-quality courses. My mission is, to teach programming to over 10.000.000 people! As you see, this is the only C# course you will ever need! You will learn all the c# fundamentals, all c# basics, and everything that you need to know to succeed in c# programming and building your own cool video games! So don’t waste any more time and start to make your dreams and ideas come true by taking this course now Who this course is for: Everyone who wants to learn C# Everyone who wants to build cross plattform video games with Unity 3D Everyone who wants to build Pc programs with a beautiful UI using WPF
facebookresearch / Reasoning MemoryProcedural Knowledge at Scale Improves ReasoningThis repository contains the minimal, end-to-end pipeline for reproducing the paper results generate a procedural knowledge datastore, build retrieval indices, run retrieval, perform model rollouts with retrieved subroutines, and filter the samples to output the final metrics.
ziy / PkbLeveraging Procedural Knowledge for Task-oriented Search
ytyz1307zzh / KOALACode for paper "Knowledge-Aware Procedural Text Understanding with Multi-Stage Training" (TheWebConf 2021)
imaddde867 / IPKEIPKE extracts Procedural Knowledge Graphs from industrial documents using task-decomposed prompting.
alcatraz47 / CSE425 04 1511944642Course: CSE425 - Concepts of Programming Language Instructor’s Name: Adjunct Associate Professor Kamruddin Nur Section: 04 Assignment: Implement searching on the given data (NCHS_-_Leading_Causes_of_Death__United_States) in Comma Separated File Format Language Used: Shell script(mandatory), C plus plus(optional), Python(optional) Submission Deadline: 15th December, 2019 Student’s Name: Md. Mahmudul Haque Id No. : 1511944642 The code of the assignment that I have implemented are on three languages and before hopping into the contrast and comparison of those languages I am here giving a brief description on my procedure of coding. I used string searching Users are offered to search on their preference of column value While a match is found the program will return the entire row of that file I used for and while loop to search for the specific string that user might look for Exceptions are handled in C plus plus and Python whereas I used if else statement to handle exception in Shell Script Aliasing are used Type casting have been used in Python Concatenation of strings are used in all the languages. Now let’s see what are the comparison and contrast between the codes of those languages! Shell script: Key Points of my Code Description #no libraries needed to import! And no curly braces In shell script no libraries are needed to import explicitly. So it is indicating that this programming language is more easy to write and read for the non-programmers also. And for the curly braces, to implement the code, prior knowledge is required. while: #no condition More liberal while handling loop. Needs user interruption or programmer’s sentinels to stop infinity cycle. If else fi, case….esac, do… done To indicate the end of if-else block I have to write ‘fi’ term after each if-else block and similar happened to case … esac term under the case block and do … done block. Not readable and to write, one has to have prior knowledge. No need to declare the type of variables In Shell Script the type of variables are not needed to be declared by the programmer explicitly. So it is loosely typed and checking runtime. And least reliable. ‘ ;; ’ after every case block To mark the end of each case Shell script needs to be said the ‘ ;; ’ . * state in case block This is indicating the general block of case if the options does not match then this block will be operated. Not so readable. foo = foo + ‘,’ Or foo = ‘,’ + foo + ‘,’ Easy to concatenate, so easy to write. Also orthogonal. No exception handling I used if else fi instead. C plus plus(C++): Key Points of my Code Description #include <bits/stdc++.h> Libraries are needed to be declared explicitly. Different than Shell Script and Python. using namespace std It is used to indicate the compiler that the standard naming convention of c++ is being used. So it is more strict in terms of language building block. Different than Shell Script and Python. int main() { …. } To execute the whole code the code must be in between the curly braces of main function block. So this is supporting abstraction. Also the statements are compound and understandable if C is known. Different than Shell Script and Python. Type checking; example - string year; Usually check the type during compile time and strongly typed. Different than Shell Script. But python is loosely typed. while(1){ .. } To operate the while loop, the coder must at least need to assign it to a true value. Expressive and writeable though always need to have some knowledge on c++ before writing code using it. Also compound. Different than Shell Script and Python. ifstream Working as a input stream to read the file. Type and work specified. Similar to Python and Shell Script try{ …if(inFile) else throw “....” } catch(const char* e){ … } To handle exception, c++ has some built in library to handle it and user either can define or not to about the variation of exception he/she wants to handle. The try block is used as experiment part whereas the catch block will catch if there is no such file according to my code. Compound with form and meaning. Almost similar to Python but Shell script does not have this facility. bool flag This is indicating that c++ is capable of using concised parameters in terms of programming paradigm. But not orthogonal as I have to handle boolean value all the time. Similar to Python in some case but Shell Script does not have it. cout or cin Capable of printing and taking input through object as c++ allows object oriented programming whereas Python also support this. Python: Key Points of my Code Description flag = True Boolean data type exists and so it is concise which is similar to C++ but Shell Script does not have this print() Capable of procedural, functional, and object oriented job. C++ is almost similar but Shell script is totally different here. try: ….. except Exception: ……. To handle exception, python has some built in library to handle it and user either can define or not to about the variation of exception he/she wants to handle. The try block is used as experiment part whereas the catch block will catch if there is no such file according to my code. Compound with form and meaning like C++. file = open("NCHS_-_Leading_Causes_of_Death__United_States.csv") Python allows aliasing whereas C++ uses referencing in alias. with file: ... Helpful while handling files. Do not need to reopen and close the file every time. C++ also have similar to this but in stream format. But Shell script is more better in handling files option = input() option = int(option) Allows type checking like C++ but loosely typed like Shell script if... elif... Have conditional statements which are also in C++ and Shell Script Conclusion: So far according to my knowledge, I found out that while interacting with file Shell script is much more easier but also Python gives a good file handling libraries now like: Pandas and C++ is more prone to let user follow the programming paradigm while handling files.
c14410312 / StackoverflowPostClassificationPost classification Experiment using Scikit learn Date 20/02/18 Dylan Butler Task The overall task of this experiment is to create a trained classifier to correctly classify whether or not a post is useful for quizes and knowledge testing of Java core concepts. Data The data for this experiment consists of a manually labelled dataset of 1500 stackoverflow posts. These posts have been filtered according to the following characteristics: They posses the structure of either a "how-to"(procedural intent) or a "why"(casual intent) type of question They have a minimum score of 7 (post score) They have not been deleted They have not been closed They have an accepted answer After extracting this data I conducted an analysis on the resulting dataset to gain a deeper understanding of the data: Extracted Data insights Group 1 (useful for quizzes): How to split a string in Java? Read and convert an input stream to a string? How to read all files in a folder in Java? How to round a number to n decimal places in Java? How to parse JSON in Java? How do I declare and initialize an array in Java? Why is it faster to process an unsorted array vs a sorted array How do I compare strings in Java? Group 2 (not useful fr quizzes): How do I fix android.os.NetworkOnMainThreadException? How do you assert that a certain exception is thrown in JUnit 4 tests? How to fix java.lang.UnsupportedClassVersionError: Unsupported major.minor version How to add local jar files to a Maven project? How do I set up IntelliJ IDEA for Android applications? How does autowiring work in Spring? How do I tell Maven to use the latest version of a dependency? Unfortunately MyApp has stopped. How can I solve this? Why is subtracting these two times (in 1927) giving a strange result? Key Findings Useless Q's A key difference I can spot is that most of the questions that pose no use are environment, framework, related and focus on a technology that uses Java. Verbs like; set-up, fix, stopped ... i.e. less java specific and more generic - used in everyday language. Useful Q's The useful questions seem to be following a pattern in which the main words in the questions (split, string, read, java, JSON, declare, initialize) are all words closely related to Java and programming concepts in general. The verbs/action words used in the useful q's are closely associated with java itself. Experiment Process Chunk tags and titles and bodies into a single body eliminate code snippets remove stop words lemmatise each body Extract the core features from the text that the algorithm can learn from Train a classifier Evaluate Improve results
adrianrm99 / Separating Knowledge[ICML 2025] Separating Knowledge with Procedural Data
jd-coderepos / Proc TmAn annotated dataset for procedural text mining from product manuals
Aryia-Behroziuan / OverviewKnowledge-representation is a field of artificial intelligence that focuses on designing computer representations that capture information about the world that can be used to solve complex problems. The justification for knowledge representation is that conventional procedural code is not the best formalism to use to solve complex problems. Knowledge representation makes complex software easier to define and maintain than procedural code and can be used in expert systems. For example, talking to experts in terms of business rules rather than code lessens the semantic gap between users and developers and makes development of complex systems more practical. Knowledge representation goes hand in hand with automated reasoning because one of the main purposes of explicitly representing knowledge is to be able to reason about that knowledge, to make inferences, assert new knowledge, etc. Virtually all knowledge representation languages have a reasoning or inference engine as part of the system.[10] A key trade-off in the design of a knowledge representation formalism is that between expressivity and practicality. The ultimate knowledge representation formalism in terms of expressive power and compactness is First Order Logic (FOL). There is no more powerful formalism than that used by mathematicians to define general propositions about the world. However, FOL has two drawbacks as a knowledge representation formalism: ease of use and practicality of implementation. First order logic can be intimidating even for many software developers. Languages that do not have the complete formal power of FOL can still provide close to the same expressive power with a user interface that is more practical for the average developer to understand. The issue of practicality of implementation is that FOL in some ways is too expressive. With FOL it is possible to create statements (e.g. quantification over infinite sets) that would cause a system to never terminate if it attempted to verify them. Thus, a subset of FOL can be both easier to use and more practical to implement. This was a driving motivation behind rule-based expert systems. IF-THEN rules provide a subset of FOL but a very useful one that is also very intuitive. The history of most of the early AI knowledge representation formalisms; from databases to semantic nets to theorem provers and production systems can be viewed as various design decisions on whether to emphasize expressive power or computability and efficiency.[11] In a key 1993 paper on the topic, Randall Davis of MIT outlined five distinct roles to analyze a knowledge representation framework:[12] A knowledge representation (KR) is most fundamentally a surrogate, a substitute for the thing itself, used to enable an entity to determine consequences by thinking rather than acting, i.e., by reasoning about the world rather than taking action in it. It is a set of ontological commitments, i.e., an answer to the question: In what terms should I think about the world? It is a fragmentary theory of intelligent reasoning, expressed in terms of three components: (i) the representation's fundamental conception of intelligent reasoning; (ii) the set of inferences the representation sanctions; and (iii) the set of inferences it recommends. It is a medium for pragmatically efficient computation, i.e., the computational environment in which thinking is accomplished. One contribution to this pragmatic efficiency is supplied by the guidance a representation provides for organizing information so as to facilitate making the recommended inferences. It is a medium of human expression, i.e., a language in which we say things about the world. Knowledge representation and reasoning are a key enabling technology for the Semantic Web. Languages based on the Frame model with automatic classification provide a layer of semantics on top of the existing Internet. Rather than searching via text strings as is typical today, it will be possible to define logical queries and find pages that map to those queries.[13] The automated reasoning component in these systems is an engine known as the classifier. Classifiers focus on the subsumption relations in a knowledge base rather than rules. A classifier can infer new classes and dynamically change the ontology as new information becomes available. This capability is ideal for the ever-changing and evolving information space of the Internet.[14] The Semantic Web integrates concepts from knowledge representation and reasoning with markup languages based on XML. The Resource Description Framework (RDF) provides the basic capabilities to define knowledge-based objects on the Internet with basic features such as Is-A relations and object properties. The Web Ontology Language (OWL) adds additional semantics and integrates with automatic classification reasoners.[15]
