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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/maoubo/sub-play

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SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems

https://github.com/maowenyu-11/rpp

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Reinforced Prompt Personalization for Recommendation with Large Language Models

https://github.com/marlbenchmark/on-policy

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The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games

https://github.com/martinballa/pytag

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PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning

https://github.com/matrl-project/matrl

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A Game-Theoretic Approach to Multi-Agent Trust Region Optimization

https://github.com/matthieu637/DFRL

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Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning

https://github.com/maxc01/addtree

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Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation

https://github.com/mazyartaghavi/Quantum-and-Neuromorphic-MARL

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Quantum Computing and Neuromorphic Computing for Safe, Reliable, and explainable Multi-Agent Reinforcement Learning: Optimal Control in Autonomous Robotics

https://github.com/mcederle99/MAD4QN-PS

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A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement Learning

https://github.com/mehdinasiri/mirror-descent-in-marl

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Heterogeneous Multi-Agent Reinforcement Learning via Mirror Descent Policy Optimization

https://github.com/metadriverse/metadrive

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MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning

https://github.com/mfigura/Resilient-consensus-based-MARL

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Resilient Consensus-based Multi-agent Reinforcement Learning with Function Approximation

https://github.com/mgerstgrasser/super

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Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning

https://github.com/michaelkoelle/marl-aquarium

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Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms

https://github.com/michaelkoelle/qmarl-evo

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Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization

https://github.com/mickelliu/selfplay-redteaming

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Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models

https://github.com/microsoft/maro

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Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations

https://github.com/microsoft/strategically_efficient_rl

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Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning

https://github.com/mila-iqia/climate-cooperation-competition

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AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N

https://github.com/ming93/Safe_reinforcement_learning

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Convergent Policy Optimization for Safe Reinforcement Learning

https://github.com/mingyukim87/npwsa

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Neural Processes with Stochastic Attention: Paying more attention to the context dataset

https://github.com/mit-wu-lab/IntersectionZoo

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IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning

https://github.com/mlii/mfrl

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Mean Field Multi-Agent Reinforcement Learning

https://github.com/mlr-org/mlrMBO

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mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions

https://github.com/mmorris44/expressive-gdns

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Universally Expressive Communication in Multi-Agent Reinforcement Learning

https://github.com/mooricAnna/HiSSD

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Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation

https://github.com/moratodpg/imp_marl

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IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL

https://github.com/mr-benjie/idrl

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Classifying Ambiguous Identities in Hidden-Role Stochastic Games with Multi-Agent Reinforcement Learning

https://github.com/mttga/pymarl_transformers

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TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems

https://github.com/mylad13/catmip

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Cooperative and Asynchronous Transformer-based Mission Planning for Heterogeneous Teams of Mobile Robots

https://github.com/mzho7212/LICA

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Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning

https://github.com/navid-naderi/GraphMIX

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Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

https://github.com/nayanadasgupta/understanding_punishment_in_mas_with_rl

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Investigating the Impact of Direct Punishment on the Emergence of Cooperation in Multi-Agent Reinforcement Learning Systems

https://github.com/newmanne/open_spiel

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Understanding Iterative Combinatorial Auction Designs via Multi-Agent Reinforcement Learning

https://github.com/news-vt/eqmarl

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eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels

https://github.com/ngminhtri0394/MACDA

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Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction

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