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- research-articleFebruary 2024
Settling decentralized multi-agent coordinated exploration by novelty sharing
AAAI'24/IAAI'24/EAAI'24: Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence and Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence and Fourteenth Symposium on Educational Advances in Artificial IntelligenceArticle No.: 1945, Pages 17444–17452https://doi.org/10.1609/aaai.v38i16.29693Exploration in decentralized cooperative multi-agent reinforcement learning faces two challenges. One is that the novelty of global states is unavailable, while the novelty of local observations is biased. The other is how agents can explore in a ...
