Play against the Gomoku AI powered by webassembly
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Updated
Dec 10, 2017 - JavaScript
Play against the Gomoku AI powered by webassembly
Simple chess engines based on sunfish
Learning go and recreating a school lab i did in game artificial intelligence for my algorithms and data structures course. Originally made in java
Theory of Computer Games 2018 http://www.iis.sinica.edu.tw/~tshsu/tcg/2018/index.html
Tic Tac Toe generalization board game
A full MTD(f) implementation. 2x faster than AlphaBeta.
This is a tic tac toe ai which is unbeatabel. It uses a algorithm called the negamax. Inorder to optimize the algorithm alpha beta pruning and transpostion tables are used.
A UCI-compatible chess engine, capable of beating (most) human players.
♟️ Ataxx [2 Player Console Game]
Das Ziel ist die Entwicklung eines Jupyter-Notebooks, in dem das Mühle-Spiel mit Hilfe von Python implementiert wird. Die Spiellogik verwendet alpha-beta-pruning und Transpositions-Tabellen.
Agent to play TUCAnts. It's a game similar to Checkers.
CS 175 Checkers AI Project
A game player for two-player perfect information games, implemented using a min-max game tree, alpha-beta pruning, and a transposition table, along with a variety of heuristics.
A C# implementation of an AI for the Cannon boardgame, with a working GUI and with various game search algorithms.
Simple AlphaZero Reinforcement Learning implementation for Go.
This homework is about Implementing a smart agent to play Quoridor, using Min-max, a heuristic function, Transposition Table and forward pruning. This homework is a part of many projects in a Fundamentals to AI course @ FUM.
MNK-game engine (generalized tic-tac-toe board game) and Player AI based on an improved Alpha-Beta pruning search algorithm with threat detection heuristic which runs in O(√(n!)*log(N+M)) time on average case
This repo contains my Bachelor Degree project. It consists in a AI which exploits A* Algorithm to generate AleaGame levels and A* Variant to solve them.
Re-designed Chess engine and converted in C++
Java chess AI using Principal Variation Splitting, Piece Square Tables, Opening Book and Tapered Evaluation.
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