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Multi-agent Reinforcement Learning

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The target of Multi-agent Reinforcement Learning is to solve complex problems by integrating multiple agents that focus on different sub-tasks. In general, there are two types of multi-agent systems: independent and cooperative systems.

Source: Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/cndota/aamas25-demar

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Dual Ensembled Multiagent Q-Learning with Hypernet Regularizer

https://github.com/codesaahil/optitraffic

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Smart Traffic Signals: Comparing MARL and Fixed-Time Strategies

https://github.com/coexistence-project/routerl

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RouteRL: Multi-agent reinforcement learning framework for urban route choice with autonomous vehicles

https://github.com/colazhang22/pps-qmix

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PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement Learning

https://github.com/cool-rr/chicken-coop

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Emergent Dominance Hierarchies in Reinforcement Learning Agents

https://github.com/cool-rr/stubborn

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Stubborn: An Environment for Evaluating Stubbornness between Agents with Aligned Incentives

https://github.com/cooperativex/socialjax

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SocialJax: An Evaluation Suite for Multi-agent Reinforcement Learning in Sequential Social Dilemmas

https://github.com/core-robotics-lab/infopg

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Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming

https://github.com/cranial-xix/marl-copa

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Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition

https://github.com/cts198859/deeprl_network

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Multi-agent Reinforcement Learning for Networked System Control

https://github.com/cugbbaiyun/hgcn-mix

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Cooperative Multi-Agent Reinforcement Learning with Hypergraph Convolution

https://github.com/cyanrain7/trust-region-policy-optimisation-in-multi-agent-reinforcement-learning

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Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning

https://github.com/cyberagentailab/m2wu

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Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games

https://github.com/daanklijn/neurocoevolution

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A coevolutionary approach to deep multi-agent reinforcement learning

https://github.com/danifuertes/top_transformer

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TOP-Former: A Multi-Agent Transformer Approach for the Team Orienteering Problem

https://github.com/data-and-decision-lab/iq-flow

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IQ-Flow: Mechanism Design for Inducing Cooperative Behavior to Self-Interested Agents in Sequential Social Dilemmas

https://github.com/datamllab/rlcard

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RLCard: A Toolkit for Reinforcement Learning in Card Games

https://github.com/daweidavidwang/mixedtrafficcontrol

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Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections

https://github.com/dawnorak/marl-kart-simulator

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Cooperation Dynamics in Multi-Agent Systems: Exploring Game-Theoretic Scenarios with Mean-Field Equilibria

https://github.com/dchen48/bnpg

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Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

https://github.com/dchen48/e3ac

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${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

https://github.com/ddaedalus/smpe

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Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration

https://github.com/decisionforce/CoPO

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Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization

https://github.com/decisionforce/metadrive

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MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning

https://github.com/deepmind/dm_control

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From Motor Control to Team Play in Simulated Humanoid Football

https://github.com/deepsota/astfocus

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Efficient Robustness Assessment via Adversarial Spatial-Temporal Focus on Videos

https://github.com/devindeng94/llm-smac

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A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models

https://github.com/devindeng94/smac-hard

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SMAC-Hard: Enabling Mixed Opponent Strategy Script and Self-play on SMAC

https://github.com/dig-beihang/ami

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Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence

https://github.com/dimonenka/mediatedmarl

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Mediated Multi-Agent Reinforcement Learning

https://github.com/djstrouse/InfoMARL

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Learning to Share and Hide Intentions using Information Regularization

https://github.com/dmitrykazhdan/MARLeME

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MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library

https://github.com/dongchen06/macacc

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Communication-Efficient Decentralized Multi-Agent Reinforcement Learning for Cooperative Adaptive Cruise Control

https://github.com/dracosource/biddinggame

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Learning to Bid Long-Term: Multi-Agent Reinforcement Learning with Long-Term and Sparse Reward in Repeated Auction Games

https://github.com/duangzhu/maexp

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MAexp: A Generic Platform for RL-based Multi-Agent Exploration

https://github.com/edun-eyes/tsc

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Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphs

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