gwstudy's repositories
Accelerating_Automatic_Search
Accelerating the Search of Differential and Linear Characteristics with the SAT Method
AlphaGo-Zero-Gobang
Meta-Zeta是一个基于强化学习的五子棋(Gobang)模型，主要用以了解AlphaGo Zero的运行原理的Demo，即神经网络是如何指导MCTS做出决策的，以及如何自我对弈学习。源码+教程
awesome-monte-carlo-tree-search-papers
A curated list of Monte Carlo tree search papers with implementations.
Book-Mathmatical-Foundation-of-Reinforcement-Learning
This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."
chatgpt_academic
科研工作专用ChatGPT拓展，特别优化学术Paper润色体验，支持自定义快捷按钮，支持markdown表格显示，Tex公式双显示，代码显示功能完善，新增本地Python工程剖析功能/自我剖析功能
deep-RL-elements
Deep RL algorithm in pytorch
Deep_RL_with_pytorch
A pytorch tutorial for DRL(Deep Reinforcement Learning)
learn-DeepRL
Modularized Implementation of Deep RL Algorithms in PyTorch
learn-reinforcement_torch_pfrl
真-极简强化学习(基于torch的强化学习框架pfrl)
learn-ReinforcementLearning1
强化学习算法库，包含了目前主流的强化学习算法(Value based and Policy basd)的代码，代码都经过调试并可以运行
learn-tensorflow_practice
tensorflow实战练习，包括强化学习、推荐系统、nlp等
mamcts-Multi
Multi-agent Monte Carlo Tree Search implementation in C++
maze-Monte_Carlo_Tree_search
Using MCTS for maze navigation
maze-solver
Developed RL algorithms like Q-Learning, Monte Carlo, and Deep Q-Network from scratch and applied them to custom maze environment
MCTS-agent-python
Monte Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree accordingly. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games and
mcts-R
Generic, parallel Monte Carlo tree search library
ml_implementation
Implementation of Machine Learning Algorithms
NSNet
[NeurIPS 2022] "NSNet: A General Neural Probabilistic Framework for Satisfiability Problems"
paper-Cloud-Workflow-Scheduling-base-on-Deep-Reinforcement-Learning
北京化工大学本科毕业设计《基于深度强化学习的云工作流调度》
paper-VN-MADDPG
Code for paper "基于多智能体深度强化学习的车联网通信资源分配优化"
PathPlannig-via-MCTS-Multi
基于蒙特卡洛树搜索算法实现多机器人区域覆盖路径规划，并将覆盖结果可视化
PathPlanning-EA
Common used path planning algorithms with animations.
PyTorchDocs
PyTorch 官方中文教程包含 60 分钟快速入门教程，强化教程，计算机视觉，自然语言处理，生成对抗网络，强化学习。欢迎 Star，Fork！
RL_path_optimization_-undergraduate
This is my undergraduate thesis for path optimization in an open, stochastic grid environment using RL methods like E-greedy strategy and Monte Carlo-Temporal Difference Hybrid
sat-benchmark
Benchmarking end-to-end SAT solvers.
sboxU
Tools for studying S-boxes
Single-Player-MCTS-network
🌳 Python implementation of single-player Monte-Carlo Tree Search.
tetris_mcts
MCTS project for Tetris