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Communication can promote coordination in cooperative Multi-Agent Reinforcement Learning (MARL).
Scaling multi-agent reinforcement learning with selective parameter sharing
Christianos F, Papoudakis G, Rahman M A, Albrecht S V · 1998
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Human-level control through deep reinforcement learning
Mnih V, Kavukcuoglu K, Silver D, Rusu A A, Veness J, Bellemare M G, Graves A, Riedmiller M A, Fidjeland A, Ostrovski G, Petersen S, Beattie C, Sadik A, Antonoglou I, King H, Kumaran D, Wierstra D, Legg S, Hassabis D · 2015
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Learning to communicate with deep multi-agent reinforcement learning
Foerster J N, Assael Y M, Freitas d N, Whiteson S · 2016
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Learning multiagent communication with backpropagation
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A Concise Introduction to Decentralized POMDPs
Oliehoek F A, Amato C · 2016
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Multi-agent actor-critic for mixed cooperative-competitive environments
Lowe R, Wu Y, Tamar A, Abbeel J H P, Mordatch I · 2017
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Population based training of neural networks
Jaderberg M, Dalibard V, Osindero S, Czarnecki W M, Donahue J, Razavi A, Vinyals O, Green T, Dunning I, Simonyan K, Fernando C, Kavukcuoglu K · 2017
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Quality and diversity optimization: A unifying modular framework
Cully A, Demiris Y · 2017
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Attention is all you need
Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez A N, Kaiser L, Polosukhin I · 2017
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Adversarial attacks and defences: A survey
Chakraborty A, Alam M, Dey V, Chattopadhyay A, Mukhopadhyay D · 2018
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Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning
Rashid T, Samvelyan M, Schroeder C, Farquhar G, Foerster J, Whiteson S · 2018
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Counterfactual multi-agent policy gradients
Foerster J N, Farquhar G, Afouras T, Nardelli N, Whiteson S · 2018
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Addressing function approximation error in actor-critic methods
Fujimoto S, Hoof v H, Meger D · 2018
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Risk averse robust adversarial reinforcement learning
Pan X, Seita D, Gao Y, Canny J · 2019
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Tarmac: Targeted multi-agent communication
Das A, Gervet T, Romoff J, Batra D, Parikh D, Rabbat M, Pineau J · 2019
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On the pitfalls of measuring emergent communication
Lowe R, Foerster J N, Boureau Y, Pineau J, Dauphin Y N · 2019
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Biases for emergent communication in multi-agent reinforcement learning
Eccles T, Bachrach Y, Lever G, Lazaridou A, Graepel T · 2019
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Efficient communication in multi-agent reinforcement learning via variance based control
Zhang S Q, Zhang Q, Lin J · 2019
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A review of cooperative multi-agent deep reinforcement learning
OroojlooyJadid A, Hajinezhad D · 2019
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Dealing with non-stationarity in multi-agent deep reinforcement learning
Papoudakis G, Christianos F, Rahman A, Albrecht S V · 2019
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Robust multi-agent reinforcement learning via minimax deep deterministic policy gradient
Li S, Wu Y, Cui X, Dong H, Fang F, Russell S · 2019
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Human-level performance in 3D multiplayer games with population-based reinforcement learning
Jaderberg M, Czarnecki W M, Dunning I, Marris L, Lever G, Castañeda A G, Beattie C, Rabinowitz N C, Morcos A S, Ruderman A, Sonnerat N, Green T, Deason L, Leibo J Z, Silver D, Hassabis D, Kavukcuoglu K, Graepel T · 2019
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The StarCraft Multi-Agent Challenge
Samvelyan M, Rashid T, Witt S. d C, Farquhar G, Nardelli N, Rudner T G, Hung C M, Torr P H, Foerster J, Whiteson S · 2019
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Autonomous skill discovery with quality-diversity and unsupervised descriptors
Cully A · 2019
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Learning individually inferred communication for multi-agent cooperation
Ding Z, Huang T, Lu Z · 2020
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Learning efficient multi-agent communication: An information bottleneck approach
Wang R, He X, Yu R, Qiu W, An B, Rabinovich Z · 2020
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Robust deep reinforcement learning against adversarial perturbations on state observations
Zhang H, Chen H, Xiao C, Li B, Liu M, Boning D S, Hsieh C · 2020
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Robust reinforcement learning on state observations with learned optimal adversary
Zhang H, Chen H, Boning D S, Hsieh C J · 2020
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On the robustness of cooperative multi-agent reinforcement learning
Lin J, Dzeparoska K, Zhang S Q, Leon-Garcia A, Papernot N · 2020
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Robust reinforcement learning using adversarial populations
Vinitsky E, Du Y, Parvate K, Jang K, Abbeel P, Bayen A · 2020
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Adaptable agent populations via a generative model of policies
Derek K, Isola P · 2021
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Maximum entropy population based training for zero-shot human-AI coordination
Zhao R, Song J, Haifeng H, Gao Y, Wu Y, Sun Z, Wei Y · 2021
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Evolutionary diversity optimization with clustering-based selection for reinforcement learning
Wang Y, Xue K, Qian C · 2021
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Quality-diversity optimization: a novel branch of stochastic optimization
Chatzilygeroudis K, Cully A, Vassiliades V, Mouret J B · 2021
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Multi-agent reinforcement learning: A selective overview of theories and algorithms
Zhang K, Yang Z, Başar T · 2021
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Learning nearly decomposable value functions via communication minimization
Wang T, Wang J, Zheng C, Zhang C · 2020
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Learning agent communication under limited bandwidth by message pruning
Mao H, Zhang Z, Xiao Z, Gong Z, Ni Y · 2020
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Learning multi-agent communication with double attentional deep reinforcement learning
Mao H, Zhang Z, Xiao Z, Gong Z, Ni Y · 2020
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Succinct and robust multi-agent communication with temporal message control
Zhang S Q, Zhang Q, Lin J · 2020
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Mitchell R, Blumenkamp J, Prorok A · 2020
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Multi-agent reinforcement learning for dynamic ocean monitoring by a swarm of buoys
Kouzehgar M, Meghjani M, Bouffanais R · 2020
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Robust multi-agent reinforcement learning with social empowerment for coordination and communication
Heiden v. d T, Salge C, Gavves E, Hoof v H · 2020
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Zhu C, Dastani M, Wang S · 2022
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Efficient multi-agent communication via shapley message value
Xue D, Yuan L, Zhang Z, Yu Y · 2022
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Efficient multi-agent communication via self-supervised information aggregation
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Multi-agent incentive communication via decentralized teammate modeling
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Robust reinforcement learning: A review of foundations and recent advances
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Sparse adversarial attack in multi-agent reinforcement learning
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Mis-spoke or mis-lead: Achieving robustness in multi-agent communicative reinforcement learning
Xue W, Qiu W, An B, Rabinovich Z, Obraztsova S, Yeo C K · 2022
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Multi-agent dynamic algorithm configuration
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Towards comprehensive testing on the robustness of cooperative multi-agent reinforcement learning
Guo J, Chen Y, Hao Y, Yin Z, Yu Y, Li S · 2022
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A survey on model-based reinforcement learning
Luo F M, Xu T, Lai H, Chen X H, Zhang W, Yu Y · 2022
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Heterogeneous multi-agent zero-shot coordination by coevolution
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Dynamics-aware quality-diversity for efficient learning of skill repertoires
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Multi-objective quality diversity optimization
Pierrot T, Richard G, Beguir K, Cully A · 2022
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Neuroevolution is a competitive alternative to reinforcement learning for skill discovery
Chalumeau F, Boige R, Lim B, Macé V, Allard M, Flajolet A, Cully A, Pierrot T · 2022
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Multi-agent deep reinforcement learning: a survey
Gronauer S, Diepold K · 2022
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Continuously discovering novel strategies via reward-switching policy optimization
Zhou Z, Fu W, Zhang B, Wu Y · 2022
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Open-environment machine learning
Zhou Z H · 2022
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Certifiably robust policy learning against adversarial multi-agent communication
Sun Y, Zheng R, Hassanzadeh P, Liang Y, Feizi S, Ganesh S, Huang F · 2023
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