A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Implementing different learning algorithms and analyzing their performance in a Markov game model called the Soccer Game

This repository analyses Strategic form games for N-player calculating various Equilibrium's, Calculate MSNE for 2-Player strategic form and zero sum game, Also contains algorithm for N-player finite Mechanism design to check if social choice function is SDSE, Ex-Post-efficient and Non-dictatorial.

Combined AI and Web-Development Subject: "A web application with AI bot for Νine Μen's Μorris board game"

Deep Reinforcement Learning algorithms to play Connect4 using a combination of Supervised Learning and Reinforcement Learning

A simple Nash Equilibrium solver for two-player zero-sum games

Tic-Tac-Toe game logic in JavaScript packaged with Minimax algorithm; built as a learning project.

Universal algorithm for deterministic resolution of alternating-turn games, based on the Gn/Px/Tz framework and backward induction.

象棋麻將 · 棋仔自摸：一個已解決博弈的完整前端實作（32/56/64張、AI、MA-FEN）

A basic Othello (Reversi) implementation that is playable by both humans and general minimax alpha-beta pruning agents

Computational game theory toolkit — Nash equilibrium solver (LP + support enumeration), replicator dynamics simulation, ESS analysis, backward induction, and VCG mechanism design implementations.

University Class AI Project using Minimax Algorithm and Heuristics to make an AI that can play the game

modeling 1v1 smogon pokémon battles with zero-sum games

Linear programming models and game theory solutions developed in R for multi-product blending, manufacturing resource allocation, and zero-sum strategic decision-making.

Nim is a mathematical game of strategy in which two players take turns removing (or "nimming") objects from distinct heaps or piles.

Equilibria computation in zero-sum games.

Python Othello Board Game to be played in Human vs. Computer mode, using alpha-beta pruning (minmax algorithm) algorithm.🎮👾🤖🏆

Some applications of optimization using linear, binary, and integer programming.

Developing algorithms for solving both strategic form and extensive form games. Seperate classes were developed to find saddle points specially for constant sum and zero sum games and to identify the nash equilibrium points of the non-zero sum games.

A Python package for game theory, especially its visualization.