SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning

[PDF] arxiv.org

A survey of progress on cooperative multi-agent reinforcement learning in open environment

L Yuan, Z Zhang, L Li, C Guan, Y Yu - arXiv preprint arXiv:2312.01058, 2023 - arxiv.org
Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
被引用次数：17 相关文章 所有 2 个版本
[PDF] arxiv.org

Jaxmarl: Multi-agent rl environments in jax

A Rutherford, B Ellis, M Gallici, J Cook, A Lupu… - arXiv preprint arXiv …, 2023 - arxiv.org
Benchmarks play an important role in the development of machine learning algorithms. For
example, research in reinforcement learning (RL) has been heavily influenced by available …
被引用次数：31 相关文章 所有 4 个版本
[PDF] arxiv.org

On stateful value factorization in multi-agent reinforcement learning

E Marchesini, A Baisero, R Bhati, C Amato - arXiv preprint arXiv …, 2024 - arxiv.org
Value factorization is a popular paradigm for designing scalable multi-agent reinforcement
learning algorithms. However, current factorization methods make choices without full …
被引用次数：2 相关文章 所有 2 个版本
[PDF] arxiv.org

Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning

A Kapoor, S Swamy, K Tessera, M Baranwal… - arXiv preprint arXiv …, 2024 - arxiv.org
In multi-agent environments, agents often struggle to learn optimal policies due to sparse or
delayed global rewards, particularly in long-horizon tasks where it is challenging to evaluate …
相关文章 所有 3 个版本
[PDF] arxiv.org

Efficiently Quantifying Individual Agent Importance in Cooperative MARL

O Mahjoub, R de Kock, S Singh, W Khlifi, A Vall… - arXiv preprint arXiv …, 2023 - arxiv.org
Measuring the contribution of individual agents is challenging in cooperative multi-agent
reinforcement learning (MARL). In cooperative MARL, team performance is typically inferred …
被引用次数：2 相关文章 所有 4 个版本

Performance Evaluation of Multi-Agent Reinforcement Learning Algorithms.

AM Abdulghani, MM Abdulghani… - … Automation & Soft …, 2024 - search.ebscohost.com
Abstract Multi-Agent Reinforcement Learning (MARL) has proven to be successful in
cooperative assignments. MARL is used to investigate how autonomous agents with the …
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