OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
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Updated
Jun 1, 2024 - C++
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
A parallel framework for population-based multi-agent reinforcement learning.
Code for ICLR 2019 paper: Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
some Multiagent enviroment in 《Multi-agent Reinforcement Learning in Sequential Social Dilemmas》 and 《Value-Decomposition Networks For Cooperative Multi-Agent Learning》
[ICRA2023] CoAlign: Robust Collaborative 3D Object Detection in Presence of Pose Errors
A multi agent path planning solution under a warehouse scenario using Q learning and transfer learning.🤖️
Training code for GA3C-CADRL algorithm (collision avoidance with deep RL)
A framework to empower forecasting using Large Language Models (LLMs)
Code for the paper Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration
A compilation of the best multi-agent papers
🛸 An implementation of multi-agent flocking formation control with specific formations that can follow a target without collision and can avoid obstacles.
Based on David Silver's paper "Cooperative Pathfinding"
A collection of multi-agent reinforcement learning OpenAI gym environments
A simple example of how to implement vector based DDPG for MARL tasks using PyTorch and a ML-Agents environment.
Easy-to-follow Pytorch tutorial Notebook for Multi-Agent-Diverse-Generative-Adversarial-Networks
Pytorch implementation of Multi-Agent Generative Adversarial Imitation Learning
基于大语言模型(LLM)和多智能体(Multi-Agent),探究AI写小说能力的边界
Agent-based modeling in JavaScript in the browser or on the server.
an implementation of CommNet
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