33 skills found · Page 2 of 2
AlexSantini10 / Maze GeneratorInteractive maze generator implemented in JavaScript using p5.js, visualizing maze construction through a depth-first search recursive backtracker algorithm.
ammahmoudi / DesignAlgorithmsHomework Solutions for Design Algorithm Course as Computer Science B.Sc. Student at Department of Mathematical Sciences, Sharif University of Technology
MinaKhamesi / Pathfinding Visualizervisualizes five pathfinding algorithms and maze generation algorithms.
tomstewart89 / Sudoku SolverA recursive-backtrack algorithm for brute force solving of sudoku puzzles
bogdanmoale / Maze SolverSimple maze-solving algorithm using recursive backtracking
Nilay0921 / Sudoku Solver CSudoku solver with implement recursive backtracking algorithm to solve a 9x9 sudoku
Natansab / Tetris⎣⎤A bin-packing algorithm to fit Tetris pieces into a box, using recursive backtracking.
dvdmc / Unity Maze GeneratorImplementation of recursive backtracker algorithm for maze generation in Unity
parthnan / SubsetSum BacktrackAlgorithmSolving the popular NP problem, The Subset Sum Problem, with an Amortized O(n) algorithm based on Recursive Backtracking. The Algorithm stood second fastest in the organized Intra-University competition.
only-dev-ops / Sudoku SolverJava Code that finds solution to a Sudoku Puzzle
The-Assembly / Code An AI Sudoku Solver In PythonSudoku is an extremely popular logic and combinatorial math-based puzzle that millions attempt on a daily basis online and on paper. In this session, we will show you how to implement a Sudoku game in Python with an in-built automatic puzzle solver (using an ML backtracking algorithm to find and evaluate candidate solutions recursively) to add some AI to our effort. Our game will allow the users to enter the numbers into the grid interactively as per the rules, with a timer running for those who wish to get competitive. For the workshop, we’ll use the free PyCharm IDE for Python (from JetBrains), so be sure to install that in advance to follow along—the IDE makes development and debugging for Python much easier. Prerequisites: —Basic knowledge of Python —PyCharm IDE (www.jetbrains.com/pycharm) ----------------------------------------- To learn more about The Assembly’s workshops, visit our website, social media or email us at workshops@theassembly.ae Our website: http://theassembly.ae Social media: —Instagram: http://instagram.com/makesmartthings —Facebook: http://fb.com/makesmartthings —Twitter: http://twitter.com/makesmartthings #Python #AI
GregoryKogan / Pac ManThis is a Pac-Man replica with map generation made in python with pygame library
nikhilagrawxl / Shortest Path And Cab BookingINTRODUCTION With so many cities in India if anyone want to know the path and about the cabs between them. The correct information is very important. The shortest path search is a problem to find a path between two nodes with a minimum number of weights, in the case of searching the fastest path between two locations on the map to travel between the two locations. One of the methods used to solve the problem of running the shortest path using the Dijkstra algorithm, the Dijkstra algorithm is the algorithm for finding the cheapest path from an initial vertex to the last vertex, this algorithm is based on the greedy technique. The Dijkstra algorithm will search for the shortest path starting from the initial node to the destination node and this algorithm will compare the smallest weight from the initial node to the destination node to find the most efficient path and at last if anyone wants to know about the cab can also get it. BACKGROUND SOFTWARE IDEAS C++, Microsoft Visual Code, Code Blocks THE PURPOSE AND BENEFITS OF SOFTWARE DEVELOPMENT The benefits of this program are by showing the route between the cities with the shortest possible distance and effectively reach the tourist destination and if anyone wants to travel by cab can also book with it. DIJKSTRA'S ALGORITHM The shortest route search includes in-graph theory material. The very algorithm famous for solving this problem is Dijkstra's algorithm. This algorithm was invented by a Dutch computer scientist who was named Edsger Dijkstra. Figure 1 below is the pseudo code of Dijkstra's algorithm. Dijkstra is the algorithm used to find the shortest path on a graph directed An example of implementing the Dijkstra algorithm is the shortest path that connects between the two different cities (Single-source Single-destination Shortest Path Problems). Procedure Dijkstra's algorithm uses a greedy strategy, where at each step, the side with the smallest weight is selected which connects an already node selected with other vertices that have not been selected. Dijkstra's algorithm requires parameters of the place of origin and place of destination. This result is the shortest distance from the place of origin to the destination and its route. BACKTRACKING ALGORITHM Backtracking is an algorithmic-technique for solving problems recursively by trying to build a solution incrementally, one piece at a time, removing those solutions that fail to satisfy the constraints of the problem at any point of time (by time, here, is referred to the time elapsed till reaching any level of the search tree). GREEDY ALGORITHM Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. So the problems where choosing locally optimal also leads to global solution are best fit for Greedy. DP ALGORITHM Dynamic Programming is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of subproblems, so that we do not have to re-compute them when needed later. This simple optimization reduces time complexities from exponential to polynomial. For example, if we write simple recursive solution for Fibonacci Numbers, we get exponential time complexity and if we optimize it by storing solutions of subproblems, time complexity reduces to linear. ANALYSIS OF REQUIREMENTS AND DESIGN OF SOFTWARE SOLUTIONS In developing this system, steps are taken namely: conducting a needs analysis, making system design/design, coding, then implementation and testing. In developing this system, steps are taken namely: conducting a needs analysis, making system design/design, coding, then implementation and testing. Needs analysis is done with data collection using google related to the system geographic information of cities. The next step in developing this system is making system design. The system design is described with the diagram as shown in Figure 2. System users are web visitors and the function it can do is search the shortest route and book the cab between them. If the user wants to find the shortest route, so the user must type one place of origin and one place of destination which are desired and than enter the details for cab booking. If all the design has been done, then proceed to check whether the system designed in terms of distance or weight is working or not. IMPLEMENTATION To use the program, it's simple enough to just access and then just look for cities in India or on the map that has been provided then type in the start and end. OUTPUT CONCLUSION From the development and testing, and validation of the system that has been carried out in connection with the search for the shortest route and book cab between them by using Dijkstra's algorithm on cities can provide. Dijkstra's algorithm is good enough to use on the shortest route search from and to cities in India
