Multi-point search algorithm using reinforcement learning

Y. Kobayashi, E. Aiyoshi

研究成果: Paper査読

抄録

This paper presents a new meta-heuristic algorithm using multi-point searches and reinforcement learning. The meta-heuristic algorithm has a layered structure that consists of a global search operation and a local search operation for every single point. The results of the local searches are used as the initial conditions of the global search. We demonstrate that the meta-heuristic algorithm with reinforcement learning can efficiently optimize various functions by applying this algorithm to some famous benchmark functions.

本文言語English
ページ3641-3644
ページ数4
出版ステータスPublished - 2005 12 1
イベントSICE Annual Conference 2005 - Okayama, Japan
継続期間: 2005 8 82005 8 10

Other

OtherSICE Annual Conference 2005
CountryJapan
CityOkayama
Period05/8/805/8/10

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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