Print Email Facebook Twitter Cooperative AI for Overcooked Title Cooperative AI for Overcooked: Multi-Agent RL with Population-Based Training Author Nestorov, Ivan (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Loftin, R.T. (mentor) Oliehoek, F.A. (mentor) Hildebrandt, K.A. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2023-06-28 Abstract In ad-hoc cooperative environments, the usage of artificial intelligence to take supportive roles and work in collaboration with humans has proven to be of great benefit. The objective of this research is to evaluate the use of population-based training for reinforcement learning agents in a simplified version of the multiplayer game - Overcooked. The method used to answer that question involves evaluating the performance of the agents when paired with a human proxy and their learning curves on different layouts. Based on the employed method, it was concluded that both PBT and other self-play agents display notable underperformance when compared to human proxies and agents trained using human data. Moreover, while the inclusion of mutated agents enhanced sample efficiency in layouts with minimal collision risks, its effect on the final performance of PBT in those layouts was negligible. However, this approach managed to improve performance in layouts where collisions were the primary limiting factor. Subject Artifical IntelligenceCollaborative AIGames To reference this document use: http://resolver.tudelft.nl/uuid:e8f04bca-cccd-4ba5-b5cf-23c52c795200 Part of collection Student theses Document type bachelor thesis Rights © 2023 Ivan Nestorov Files PDF Final_Paper_Ivan_Nestorov.pdf 744.58 KB Close viewer /islandora/object/uuid:e8f04bca-cccd-4ba5-b5cf-23c52c795200/datastream/OBJ/view