ERD

Multi-Agent MDP Homomorphic Networks

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Updated at: 27-04-2024

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Decentralized MCTS via Learned Teammate Models

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Influence-Based Abstraction in Deep Reinforcement Learning

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Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning

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Loss Bounds for Approximate Influence-Based Abstraction

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Maximizing Information Gain in Partially Observable Environments via Prediction Reward

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Online Planning in POMDPs with Self-Improving Simulators

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Multi Robot Surveillance and Planning in Limited Communication Environments

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Model-Based Reinforcement Learning with State Abstraction: A Survey.

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Multi-agent active perception with prediction rewards

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Alternating Maximization with Behavioral Cloning

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A Sufficient Statistic for Influence in Structured Multiagent Environments

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General-Sum Multi-Agent Continuous Inverse Optimal Control

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Influence-aware memory architectures for deep reinforcement learning in POMDPs

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Analog Circuit Design with Dyna-Style Reinforcement Learning

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Comparing Exploration Approaches in Deep Reinforcement Learning for Traffic Light Control.

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Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems

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Beyond Local Nash Equilibria for Adversarial Networks

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A Sufficient Statistic for Influence in Structured Multiagent Environments

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Bayesian Reinforcement Learning in Factored POMDPs

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Interactive Learning and Decision Making: Foundations, Insights & Challenges

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The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

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Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity?

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Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

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Poincaré-Bendixson Limit Sets in Multi-Agent Learning

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Bayesian Reinforcement Learning in Factored POMDPs

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The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

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Beyond Local Nash Equilibria for Adversarial Networks

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Influence-aware Memory Architectures for Deep Reinforcement Learning

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Difference rewards policy gradients

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Resources

Selected filters:

Multi-Agent MDP Homomorphic Networks

Decentralized MCTS via Learned Teammate Models

Influence-Based Abstraction in Deep Reinforcement Learning

Analysing factorizations of action-value networks for cooperative multi-agent reinforcement learning

Loss Bounds for Approximate Influence-Based Abstraction

Maximizing Information Gain in Partially Observable Environments via Prediction Reward

Online Planning in POMDPs with Self-Improving Simulators

Multi Robot Surveillance and Planning in Limited Communication Environments

Model-Based Reinforcement Learning with State Abstraction: A Survey.

Multi-agent active perception with prediction rewards

Alternating Maximization with Behavioral Cloning

A Sufficient Statistic for Influence in Structured Multiagent Environments

General-Sum Multi-Agent Continuous Inverse Optimal Control

Influence-aware memory architectures for deep reinforcement learning in POMDPs

Analog Circuit Design with Dyna-Style Reinforcement Learning

Comparing Exploration Approaches in Deep Reinforcement Learning for Traffic Light Control.

Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems

Beyond Local Nash Equilibria for Adversarial Networks

A Sufficient Statistic for Influence in Structured Multiagent Environments

Bayesian Reinforcement Learning in Factored POMDPs

Interactive Learning and Decision Making: Foundations, Insights & Challenges

The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity?

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

Poincaré-Bendixson Limit Sets in Multi-Agent Learning

Bayesian Reinforcement Learning in Factored POMDPs

The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

Beyond Local Nash Equilibria for Adversarial Networks

Influence-aware Memory Architectures for Deep Reinforcement Learning

Difference rewards policy gradients