Multi-agent Reinforcement Learning

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

Papers

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Showing 1191–1200 of 1718 papers

Title	Date	Tasks	Status
PooL: Pheromone-inspired Communication Framework forLarge Scale Multi-Agent Reinforcement Learning	Feb 20, 2022	Multi-agent Reinforcement LearningQ-Learning	—Unverified
Shaping Advice in Deep Reinforcement Learning	Feb 19, 2022	Deep Reinforcement LearningMulti-agent Reinforcement Learning	CodeCode Available
Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games	Feb 18, 2022	Multi-agent Reinforcement Learning	—Unverified
Motivating Physical Activity via Competitive Human-Robot Interaction	Feb 14, 2022	Multi-agent Reinforcement LearningReinforcement Learning (RL)	—Unverified
Understanding Value Decomposition Algorithms in Deep Cooperative Multi-Agent Reinforcement Learning	Feb 10, 2022	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified
Group-Agent Reinforcement Learning	Feb 10, 2022	Multi-agent Reinforcement Learningreinforcement-learning	—Unverified
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence	Feb 8, 2022	Multi-agent Reinforcement LearningPolicy Gradient Methods	—Unverified
Attacking c-MARL More Effectively: A Data Driven Approach	Feb 7, 2022	Adversarial AttackMulti-agent Reinforcement Learning	—Unverified
Generalization in Cooperative Multi-Agent Systems	Jan 31, 2022	Generalization BoundsMulti-agent Reinforcement Learning	—Unverified
Trust Region Bounds for Decentralized PPO Under Non-stationarity	Jan 31, 2022	Multi-agent Reinforcement Learning	—Unverified

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All datasets ParticleEnvs Cooperative Communication SMAC-Exp UAV Logistics

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MATD3	final agent reward	-14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRIMA	Median Win Rate	15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Fusion-Multi-Actor-Attention-Critic	Average Reward	39	—	Unverified