Multi Agent Reinforcement Learning Papers

• An Analysis of Stochastic Game Theory for Multiagent Reinforcement Learning
• Coordination Guided Reinforcement Learning
• A comprehensive survey of multi-agent reinforcement learning
• Multi-agent reinforcement learning: An overview
• Multi-agent Inverse Reinforcement Learning for Two-person Zero-sum Games
• Comparison of Multi-agent and Single-agent Inverse Learning on a Simulated Soccer Example
• Decentralised Multi-Agent Reinforcement Learning for Dynamic and Uncertain Environments
• Multi-agent Reinforcement Learning with Sparse Interactions by Negotiation and Knowledge Transfer
• Multiagent Cooperation and Competition with Deep Reinforcement Learning
• Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks
• Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
• Learning to Communicate with Deep Multi-Agent Reinforcement Learning
• Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving
• Multi-agent Reinforcement Learning in Sequential Social Dilemmas
• Collaborative Deep Reinforcement Learning for Joint Object Search
• Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
• Robust Adversarial Reinforcement Learning
• Coordinated Multi-Agent Imitation Learning
• Emergence of Grounded Compositional Language in Multi-Agent Populations
• Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
• Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning
• Multiagent Bidirectionally-Coordinated Nets
• Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
• Learning with Opponent-Learning Awareness
• Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
• Emergent Complexity via Multi-Agent Competition
• A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
• MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence
• Mean Field Multi-Agent Reinforcement Learning
• Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
• CLEANing the Reward: Counterfactual Actions Remove Exploratory Action Noise in Multiagent Learning
• Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games
• Extending Q-Learning to General Adaptive Multi-Agent Systems
• Learning Multiagent Communication with Backpropagation
• Cooperative Inverse Reinforcement Learning
• Reinforcement Learning of Coordination in Cooperative Multi-agent Systems
• The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
• Hierarchical MultiAgent Reinforcement Learning
• Multiagent Learning: Basics, Challenges, and Prospects
• Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty
• Asymmetric multiagent reinforcement learning
• AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Opponents
• Multi-Agent Reinforcement Learning in Common Interest and Fixed Sum Stochastic Games: An Experimental Study
• Coordination in Multiagent Reinforcement Learning: A Bayesian Approach
• Multi-Agent Stochastic Simulation of Occupants for Building Simulation
• Extending No-MASS: Multi-Agent Stochastic Simulation for Demand Response of residential appliances
• Efficient Distributed Reinforcement Learning Through Agreement
• Opponent Modeling in Deep Reinforcement Learning
• Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols
• Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
• Emergent Communication through Negotiation
• Transfer Learning in Multi-agent Reinforcement Learning Domains
• Fictitious Self-Play in Extensive-Form Games
• Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
• Transfer Learning for Multi-agent Coordination
• Coordinated Reinforcement Learning
• Markov Security Games: Learning in Spatial Security Problems
• Collaborative Multiagent Reinforcement Learning by Payoff Propagation
• From Single-Agent to Multi-Agent Reinforcement Learning: Foundational Concepts and Methods
• Markov games as a framework for multi-agent reinforcement learning
• Multi-Agent Inverse Reinforcement Learning
• Reinforcement Social Learning of Coordination in Networked Cooperative Multiagent Systems
• Deep Reinforcement Learning Variants of Multi-Agent Learning Algorithms
• Multi-Agent Cooperation and the Emergence of (Natural) Language
• Multi-Agent Reinforcement Learning
• Reinforcement Learning in Partially Observable Multiagent Settings: Monte Carlo Exploring Policies with PAC Bounds
• Simultaneously Learning and Advising in Multiagent Reinforcement Learning
• Cooperative Multi-Agent Learning: The State of the Art
• Accelerating Multi-agent Reinforcement Learning with Dynamic Co-learning