NeurIPS 2023 Multiple Agents

Some MARL papers that might be related and interesting to read.

Ke Fang, Guohao Li, Philip Han

Created over 1 year ago

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CAMEL: Communicative Agents for "Mind" Exploration of Large Language M...

The rapid advancement of chat-based language models has led to remarkable progress in complex task-s...

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Reflexion: Language Agents with Verbal Reinforcement Learning

Large language models (LLMs) have been increasingly used to interact with external environments (e.g...

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Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates wit...

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity for NeurIPS ...

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How2comm: Communication-Efficient and Collaboration-Pragmatic...

Multi-agent collaborative perception has recently received widespread attention as an emerging appli...

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OFCOURSE: A Multi-Agent Reinforcement Learning Environment for...

The dramatic growth of global e-commerce has led to a surge in demand for efficient and cost-effecti...

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Multi-Agent Learning with Heterogeneous Linear Contextual Bandits

As trained intelligent systems become increasingly pervasive, multiagent learning has emerged as a p...

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Selectively Sharing Experiences Improves Multi-Agent Reinforcement Lea...

We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized Experience Relay, in w...

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Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Loc...

Offline reinforcement learning (RL) has received considerable attention in recent years due to its a...

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Group-oriented Cooperation in Multi-Agent Reinforcement Learning

We propose an automatic grouping mechanism in cooperative MARL, which dynamically adjusts the groupi...

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Large Language Models Are Semi-Parametric Reinforcement Learning Agent...

Inspired by the insights in cognitive science with respect to human memory and reasoning mechanism, ...

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Two Heads are Better Than One: A Simple Exploration Framework for...

Exploration strategy plays an important role in reinforcement learning, especially in sparse-reward ...

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SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex ...

We introduce SwiftSage, a novel agent framework inspired by the dual-process theory of human cogniti...

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Counterfactual Conservative Q Learning for Offline Multi-agent Reinfor...

Offline multi-agent reinforcement learning is challenging due to the coupling effect of both distrib...

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Hierarchical Multi-Agent Skill Discovery

Skill discovery has shown significant progress in unsupervised reinforcement learning.

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Combinatorial Group Testing with Selfish Agents

We study the Combinatorial Group Testing (CGT) problem in a novel game-theoretic framework, with a s...

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