A rust implementation of the famous 2048 game
CSE 571 Artificial Intelligence
A set of AIs for the 2048 tile-merging game. Includes an expectimax strategy that reaches 16384 with 34.6% success and an ML model trained with temporal difference learning.
A simplified version of Go game in Python, with AI agents built-in and GUI to play.
Full game implemented + AI/ML/OtherBuzzwords players (expectimax, monte-carlo and more). Fork me!
Implementation of many popular AI algorithms to play the game of Pacman such as Minimax, Expectimax and Greedy.
Bots for the board game quoridor implemented using four algorithms: minimax, minimax with alpha beta pruning, expectimax and monte carlo tree search.
一个100KB的内置强大AI的安卓2048小游戏。每秒5次移动的情况下，AI有94%概率合成16384。A 100KB android 2048 game with a powerful AI !!!
Ai agent for pacman
My solutions to projects 1, 2 & 3 of Berkeley's AI course
2048 game solved with Expectimax
A multi-agent implementation of the game Connect-4 using MCTS, Minimax and Exptimax algorithms.
Pokémon battles simulator, with the use of MiniMax-Type algorithms (Artificial Intelligence project)
Variance of the board game Settlers of Catan, with a University/Campus theme
Solutions to Pacman AI Multi-Agent Search problems
A 2048 AI, written in C++ using an ASCII interface and the Expectimax algorithm.
Final project of the course Introduction to Artificial Intelligence of NCTU
Collection of AI algorithms to solve/optimize 2048 games.
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