Timezone: »
Multi-agent deep reinforcement learning (MARL) suffers from a lack of commonly-used evaluation tasks and criteria, making comparisons between approaches difficult. In this work, we provide a systematic evaluation and comparison of three different classes of MARL algorithms (independent learning, centralised multi-agent policy gradient, value decomposition) in a diverse range of cooperative multi-agent learning tasks. Our experiments serve as a reference for the expected performance of algorithms across different learning tasks, and we provide insights regarding the effectiveness of different learning approaches. We open-source EPyMARL, which extends the PyMARL codebase to include additional algorithms and allow for flexible configuration of algorithm implementation details such as parameter sharing. Finally, we open-source two environments for multi-agent research which focus on coordination under sparse rewards.
Author Information
Georgios Papoudakis (University of Edinburgh)
Filippos Christianos (University of Edinburgh)
Lukas Schäfer (University of Edinburgh)
Stefano Albrecht (University of Edinburgh)
More from the Same Authors
-
2021 : Robust On-Policy Data Collection for Data-Efficient Policy Evaluation »
Rujie Zhong · Josiah Hanna · Lukas Schäfer · Stefano Albrecht -
2022 : Enhancing Transfer of Reinforcement Learning Agents with Abstract Contextual Embeddings »
Guy Azran · Mohamad Hosein Danesh · Stefano Albrecht · Sarah Keren -
2022 : Verifiable Goal Recognition for Autonomous Driving with Occlusions »
Cillian Brewitt · Massimiliano Tamborski · Stefano Albrecht -
2022 : Sample Relationships through the Lens of Learning Dynamics with Label Information »
Shangmin Guo · Yi Ren · Stefano Albrecht · Kenny Smith -
2022 : Learning Representations for Reinforcement Learning with Hierarchical Forward Models »
Trevor McInroe · Lukas Schäfer · Stefano Albrecht -
2022 : Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning »
Mhairi Dunion · Trevor McInroe · Kevin Sebastian Luck · Josiah Hanna · Stefano Albrecht -
2023 Poster: Conditional Mutual Information for Disentangled Representations in Reinforcement Learning »
Mhairi Dunion · Trevor McInroe · Kevin Sebastian Luck · Josiah Hanna · Stefano Albrecht -
2022 Poster: Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning »
Rujie Zhong · Duohan Zhang · Lukas Schäfer · Stefano Albrecht · Josiah Hanna -
2021 Poster: Agent Modelling under Partial Observability for Deep Reinforcement Learning »
Georgios Papoudakis · Filippos Christianos · Stefano Albrecht -
2020 Poster: Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning »
Filippos Christianos · Lukas Schäfer · Stefano Albrecht