Cooperative behavior control of robot group using stress antibody allotment reward

Sung Geun Kim*, Shinya Taguchi, Su Ill Hong, Hee Hyol Lee

*この研究の対応する著者

研究成果査読

4 被引用数 (Scopus)

抄録

Lately, development in robotics for utilizing in both industry and home is in much progress. In this research, a group of robots is made to handle relatively complicated tasks. Cooperative action among robots is one of the research areas in robotics that is progressing remarkably well. Reinforcement learning is known as a common approach in robotics for deploying acquisition of action under dynamic environment. However, until recently, reinforcement learning is only applied to one agent problem. In multi-agent environment where plural robots exist, it was difficult to differentiate between learning of achievement of task and learning of performing cooperative action. This paper introduces a method of implementing reinforcement learning to induce cooperation among a group of robots where its task is to transport luggage of various weights to a destination. The general Q-learning method is used as a learning algorithm. Also, the switching of learning mode is proposed for reduction of learning time and learning area. Finally, grid world simulation is carried out to evaluate the proposed methods.

本文言語English
ページ(範囲)16-21
ページ数6
ジャーナルArtificial Life and Robotics
19
1
DOI
出版ステータスPublished - 2014 2 1

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 人工知能

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