Achieving Robustness and Generalization in MARL for Sequential Social Dilemmas through Bilinear Value Networks
This thesis presents a novel approach for training multi-agent reinforcement learning (MARL) agents that are robust to different unforeseen gameplay strategies in sequential social dilemma (SSD) games. Recent literature has demonstrated that reward shaping can not only be used to enable MARL agents...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/152745 |