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1 Ergebnisse
1
Maximizing Information Gain in Partially Observable Environ..:
, In:
Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems
,
Satsangi, Yash
;
Lim, Sungsu
;
Whiteson, Shimon
.. - p. 1215-1223 , 2020
Link:
https://dl.acm.org/doi/10.5555/3398761.3398902
RT T1 <cTitle>Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems</cTitle>: T1 <Title>Maximizing Information Gain in Partially Observable Environments via Prediction Rewards</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3398902&Exemplar=1&LAN=DE A1 Satsangi, Yash A1 Lim, Sungsu A1 Whiteson, Shimon A1 Oliehoek, Frans A. A1 White, Martha PB International Foundation for Autonomous Agents and Multiagent Systems YR 2020 K1 information gain K1 partial observability K1 reinforcement learning K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Reinforcement learning SP 1215 OP 1223 LK http://dx.doi.org/https://dl.acm.org/doi/10.5555/3398761.3398902 DO https://dl.acm.org/doi/10.5555/3398761.3398902 SF ELIB - SuUB Bremen
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