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How an adaptive learning rate benefits neuro-fuzzy reinforcement learning systems

Lecture notes in computer science Volume 8794 Page 324-331
published_at 2014-10
2015010172.pdf
[fulltext] 789 KB
Title
How an adaptive learning rate benefits neuro-fuzzy reinforcement learning systems
Creators Kuremoto Takashi
Creators Obayashi Masanao
Creators Kobayashi Kunikazu
Creators Mabu Shingo
Creator Keywords
Neuro-fuzzy system swarm behavior reinforcement learning (RL) multi-agent system (MAS) adaptive learning rate (ALR) goal-exploration problem
Languages eng
Resource Type journal article
Publishers Springer
Date Issued 2014-10
File Version Version of Record
Access Rights open access
Relations
[ISSN]0302-9743
[ISSN]1611-3349
[NCID]AA12401092
10.1007/978-3-319-11857-4_37
[isVersionOf] [URI]http://link.springer.com/bookseries/558
Schools 大学院理工学研究科(工学)