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
C++17 command-line Buckshot Roulette: a move advisor built on expectiminimax over each seat's information, ranking the available moves by the chance of winning the round under a stated opponent model, and a playable opponent.
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.
You can play the Syrian Persis board game against my AI agent that was built with Expectiminimax Algorithm
The Royal Game of Ur with expectiminimax AI.
2048 Pseudo AI | 15-112 Term Project (Spring 2019)
Simplified Monopoly board game, that is played by 2 expectiminimax agents.
AI 2048 solver
Implementation of the game of Yahtzee using the expecti-minimax algorithm
Offline-first Royal Game of Ur with search, self-play ML, and solved-game-distilled Oracle AI in React, Rust/WASM, and Cloudflare Workers.
This project is based on the UC Berkeley CS188 Pacman AI framework, implementing and testing algorithms and multi-agent search strategies for Pacman.
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)
Course in Artificial Intelligence for the Winter semester 2022 - 2023 in Informatics, NKUA
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