Coordination approaches
Graph-based agent models
Non-stationarity challenges
Sanchez-Gonzalez et al. - 2018 - Graph networks as learnable physics engines for in
Yang et al. - 2019 - Bayes-ToMoP A Fast Detection and Best Response Al
Veličković et al. - 2018 - Graph Attention Networks
Grover et al. - Evaluating Generalization in Multiagent Systems us
Bargiacchi et al. - 2020 - Model-based Multi-Agent Reinforcement Learning wit
Kipf and Welling - 2016 - Variational Graph Auto-Encoders
Chen et al. - 2019 - Adversarial attack and defense in reinforcement le
Yang and Wang - 2021 - An Overview of Multi-Agent Reinforcement Learning
Seo et al. - 2016 - Structured Sequence Modeling with Graph Convolutio
Wang et al. - 2018 - NERVENET LEARNING STRUCTURED POLICY WITH GRAPH NE
Niu et al. - 2021 - Multi-Agent Graph-Attention Communication and Team
Battaglia et al. - 2016 - Interaction Networks for Learning about Objects, R
Mazzaglia et al. - 2022 - The Free Energy Principle for Perception and Actio
Laurent et al. - 2011 - The world of Independent learners is not Markovian
Li et al. - 2021 - Deep Implicit Coordination Graphs for Multi-agent
Graber and Schwing - 2020 - Dynamic Neural Relational Inference
He et al. - 2016 - Opponent Modeling in Deep Reinforcement Learning
Wang and van Hoof - 2021 - Model-based Meta Reinforcement Learning using Grap
Hernandez-Leal et al. - 2019 - A Survey and Critique of Multiagent Deep Reinforce
Gilmer et al. - 2017 - Neural Message Passing for Quantum Chemistry
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