mcts-simple is a Python3 library that allows reinforcement learning problems to be solved easily with its implementations of Monte Carlo Tree Search.
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Updated
Jun 12, 2024 - Python
mcts-simple is a Python3 library that allows reinforcement learning problems to be solved easily with its implementations of Monte Carlo Tree Search.
This repository contains the material used to complete my Thesis for my BSc in Data Science and AI. My thesis attempts to explore the work started by previous alumni at my faculty which covered an algorithm variant of MCTS implementing a technique known as Sequential Halving, and I will attempt an algorithm using time constraints
[ICML'24 Oral] Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios
AlphaZero based engine for the game of Go (圍棋/围棋).
Sentiment Analysis & Monte Carlo Tree Search with Nested Rollout Policy Adaptation for Business
[ICML'24 Oral] Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Projects in IT3105 AI programming, a second degree level subject at NTNU, 2024
This is a python implementation of the board game Othello with Negamax and MCTS. Powered by Numba for high-performance computation.
The best FFXIV crafting solver via hardware accelerated MCTS.
The decision-making of multiple vehicles at intersection bases on level-k game and MCTS
MiniZero: An AlphaZero and MuZero Training Framework
Companion repository of the "Dancer in the Dark" paper.
#include-only, single header, custom written ai that can play ANY turn based game, including Boardgames, Card-games, hidden-info games, multiplayer games, and games with randomness.
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