Playing a Strategy Game with Knowledge-Based Reinforcement Learning

This paper presents knowledge-based reinforcement learning (KB-RL) as a method that combines a knowledge-based approach and a reinforcement learning (RL) technique into one method for intelligent problem solving. The proposed approach focuses on multi-expert knowledge acquisition, with the RL being...

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Veröffentlicht in:	SN computer science Jg. 1; H. 2; S. 78
Hauptverfasser:	Voss, Viktor, Nechepurenko, Liudmyla, Schaefer, Rudi, Bauer, Steffen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Singapore 01.03.2020 Springer Nature B.V
Schlagworte:	Algorithms Artificial intelligence Automation Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Deep learning Games Information Systems and Communication Service Knowledge acquisition Knowledge bases (artificial intelligence) Knowledge representation Machine learning Neural networks Ontology Original Research Pattern Recognition and Graphics Problem solving Semantics Software Software Engineering/Programming and Operating Systems Strategy Vision Knowledge-based systems Multi-expert knowledge base Conflict resolution Reinforcement learning
ISSN:	2662-995X, 2661-8907
Online-Zugang:	Volltext
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