A rust implementation of the famous 2048 game
-
Updated
Oct 10, 2023 - Rust
A rust implementation of the famous 2048 game
A 2D JavaFX implementation of one of the most popular and old board games. The AI player's moves are calculated using the expectiminimax algorithm.
Implementations of artificial intelligence agents that plays Pac-Man
A highly modular Object-Oriented AI framework and interactive lab implemented in Python. Features automated benchmarking, pluggable solver engines, and interactive Pygame visualizers for Search, CSPs, Optimization, and Adversarial Games.
基于 Expectiminimax 的西洋双陆棋博弈,参考了alexandremartens 、chanddu等大佬的有关项目
You can play the Syrian Persis board game against my AI agent that was built with Expectiminimax Algorithm
Implemented a expectiminimax agent (2-ply search) with alpha – beta pruning and forward pruning (to reduce the branching factor in the game tree) to determine the best move give the state of the board.
The Royal Game of Ur with expectiminimax AI.
Autonomous, game-theoretic Pokémon Showdown AI powered by Simultaneous Expectiminimax, Set-Transformer neural policy pruning (ONNX), inverse damage calculations, and Smogon metagame priors.
2048 Pseudo AI | 15-112 Term Project (Spring 2019)
Simplified Monopoly board game, that is played by 2 expectiminimax agents.
Offline-first Royal Game of Ur with search, self-play ML, and solved-game-distilled Oracle AI in React, Rust/WASM, and Cloudflare Workers.
AI 2048 solver
Implementation of the game of Yahtzee using the expecti-minimax algorithm
This project is based on the UC Berkeley CS188 Pacman AI framework, implementing and testing algorithms and multi-agent search strategies for Pacman.
A Banqi (Half Chess / Chinese Dark Chess) engine in Rust
A Java console-based Ludo game with human players, bot players, core Ludo rules, and AI decision-making using Expectiminimax.
2048 with expectimax for the autoplay (botSolver/AI)
Add a description, image, and links to the expectiminimax topic page so that developers can more easily learn about it.
To associate your repository with the expectiminimax topic, visit your repo's landing page and select "manage topics."