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The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
Partially Observable Markov Decision Processes (POMDPs) are used to model environments where the state cannot be perceived, …
Raphael Avalos, Florent Delgrange, Ann Nowe, Guillermo Perez, Diederik M. Roijers
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Laser Learning Environment: A new environment for coordination-critical multi-agent tasks
We introduce the Laser Learning Environment (LLE), a collaborative multi-agent reinforcement learning environment in which coordination …
Yannick Molinghen, Raphael Avalos, Mark Van Achter, Ann Nowe, Tom Lenaerts
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Exploration and Communication for Partially Observable Collaborative Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) enables us to create adaptive agents in challenging environments, even when the agents have …
Raphael Avalos
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Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) enables us to create adaptive agents in challenging environments, even when the agents have …
Raphael Avalos, Mathieu Reymond, Ann Nowe, Diederik M. Roijers
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