LLM|based Multi|Agent Reinforcement Learning

LLM-based Multi-Agent Reinforcement Learning: Current and Future ...

In this letter, we survey the existing LLM-based single-agent and multi-agent RL frameworks and provide potential research directions for future research.

Name Best LLM-powered Multi Agent RL papers you came across

r/reinforcementlearning - My first use of reinforcement learning to solve my own problem! 170 upvotes · 15 comments. r/reinforcementlearning ...

LLM-based Multi-Agent Reinforcement Learning: Current and Future ...

Although research on LLM-as-an-agent has shown that. LLM can be applied to Reinforcement Learning (RL) and achieve decent results, the extension ...

LLM reinforcement learning: What is Essential in 2024 - Medium

Multi-Agent Reinforcement Learning (MARL) expands RL to settings featuring multiple interacting agents, each with its objectives and policies.

From Deep Reinforcement Learning to LLM-based Agents - YouTube

2023 AI Seminar Series: Stefano Albrecht - Deep Reinforcement Learning for Multi-Agent Interaction. Amii•1.3K views

WindyLab/LLM-RL-Papers - GitHub

Research Review. LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions; A Survey on Large Language Model-Based Game Agents ...

Multi-agent reinforcement learning - Wikipedia

Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that ...

Leveraging Large Language Models for Optimised Coordination in...

... multi-agent reinforcement learning by leveraging LLM. FAMA consists of an actor where LLM can be used to infer probability of each action, a communication ...

Paper list of multi-agent reinforcement learning (MARL) - GitHub

This is a collection of research and review papers of multi-agent reinforcement learning (MARL). The Papers are sorted by time.

LLM-based Multi-Agent Reinforcement Learning - arxiv-sanity

In this letter, we survey the existing LLM-based single-agent and multi-agent RL frameworks and provide potential research directions for future research.

LlamaGym – fine-tune LLM agents with online reinforcement learning

It does simplify LLM agent inference on Gym environments but the main technical contribution is reducing your would-be code overhead for online RL.

[PDF] LLM-based Multi-Agent Reinforcement Learning

This letter surveys the existing LLM-based single-agent and multi-agent RL frameworks and provides potential research directions for future research, ...

Theory of Mind for Multi-Agent Collaboration via Large Language ...

This study evaluates LLM-based agents in a multi-agent cooperative text ... Multi-Agent Reinforcement Learning (MARL) and planning-based baselines. We ...

Theory of Mind for Multi-Agent Collaboration via Large Language ...

... Multi-Agent Reinforcement Learning (MARL) and planning-based baselines. We observed evidence of emergent collaborative behaviors and high-order Theory of ...

Why the future is agentic: An overview of Multi-Agent LLM Systems

... based approaches in our Deep Dive: Prompt Optimization with Reinforcement Learning in Large Language Model. A new era of agentic LLMs. But ...

MALib: A Parallel Framework for Population-based Multi-agent ...

Population-based multi-agent reinforcement learning (PB-MARL) encompasses a range of methods that merge dynamic population selection with multi-agent ...

Boosting Embodied Reasoning in LLMs in Multi-agent Mixed ...

... LLM-based agent for mixed-incentive multi-agent environments ... Options as responses: Ground- ing behavioural hierarchies in multi-agent reinforcement learning.

A survey on multi-agent reinforcement learning and its application

On the other hand, MARL-based swarm behaviors have emerged as a prominent research area. [20] introduced a Q-learning-based algorithm for swarm systems named Q- ...

Multi-agent LLMs in 2024 [+frameworks] - SuperAnnotate

Hierarchical multi-agent RL: Hierarchical multi-agent reinforcement learning ... llm active learning. LLM. Active learning for LLMs. Unlocking ...

Reinforcement Learning Based Multi-Agent Resilient Control

Recent advances in Multi-agent Reinforcement Learning (MARL) have made it possible to implement various tasks in cooperative as well as ...