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Methods in Adversarial Intelligent Game:A Holistic Comparat..:
YUAN Wei-lin
;
LUO Jun-ren
;
LU Li-na
...
https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-8-191.pdf. , 2022
Link:
https://doi.org/10.11896/jsjkx.220200174
RT Journal T1 <Title>Methods in Adversarial Intelligent Game:A Holistic Comparative Analysis from Perspective of Game Theory and Reinforcement Learning</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:8e46dedfc5094dcbae79317d6aa721b2&Exemplar=1&LAN=DE A1 YUAN Wei-lin A1 LUO Jun-ren A1 LU Li-na A1 CHEN Jia-xing A1 ZHANG Wan-peng A1 CHEN Jing PB Editorial office of Computer Science YR 2022 K1 adversarial intelligent game|counterfactual regret minimization|fictitious self-play|nash equilibrium|reinforcement learning K1 Computer software K1 QA76.75-76.765 K1 Technology (General) K1 T1-995 JF https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-8-191.pdf LK http://dx.doi.org/https://doi.org/10.11896/jsjkx.220200174 DO https://doi.org/10.11896/jsjkx.220200174 SF ELIB - SuUB Bremen
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