The lecture notes for my discrete mathematics classes.
Combinatorial Game Theory toolkit
Ludology is a Python package for combinatorial game theory.
Rust software for solving impartial games.
A Deep Reinforcement Learning environment using generalized tic-tac-toe.
Solve any sequential game.
basic nim simulator for all you Sprague-Grundy stans. will mostly always win against you, unless you know how to draw.
A coding project for Math 480 Combinatorial Game Theory (Spring 2024) exploring the relationship between AI and combinatorial game theory. Specifically, I will study the game Toads and Frogs by implementing a DQN reinforcement learning algorithm from scratch.
A machine learning environment and interactive simulator for infinite grid parity jump puzzles (e.g., Conway's Soldiers, Peg Solitaire) based on point reflection symmetry.
Standalone C++23 solver and interactive CLI for undirected vertex geography using exact matching-based evaluation.
Formalization of Misère Combinatorial Game Theory
Comprehensive Qwirkle RL agent application. We'll use Monte Carlo Tree Search (MCTS) combined with Q-Learning - the best approaches for tile-placement games with high branching factors.
Floe - an original two-player abstract strategy game with no luck and no draws. Spread your floe, freeze the water, lock your opponent in. Proprietary, all rights reserved.
RPG dice notation evaluator with exact distributions in pure Standard ML
Complete Chess Implementation Gardner's 5x5 Minichess - Full chess rules on a 5x5 board All 6 piece types: King, Queen, Rook, Bishop, Knight, Pawn Proper move generation including: Pawn promotion (to Q/R/B/N) Special pawn captures Check/checkmate detection Stalemate handling.
This contains the code for our paper: Domineering games with minimal number of moves.
Classic Nim Rules - 3 customizable piles, take any number from one pile per turn, last to take loses Q-Learning Agents - Two independent agents that learn optimal strategy through self-play
Deep Search: 150 MCTS simulations per move explores thousands of positions Pattern Learning: Policy network learns winning move sequences Forced Captures: Properly implements mandatory jump rules King Awareness: Values promotions and king positioning Multi-jump Sequences: Handles complex capture chains Center Control: Mimics grandmaster position.
Strongly solving Dōbutsu Shōgi: a from-scratch Rust tablebase, a probe API, and a lichess-style explorer.
Add a description, image, and links to the combinatorial-game-theory topic page so that developers can more easily learn about it.
To associate your repository with the combinatorial-game-theory topic, visit your repo's landing page and select "manage topics."