Tug-of-war model for multi-armed bandit problem

Song Ju Kim, Masashi Aono, Masahiko Hara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

We propose a model - the "tug-of-war (TOW) model" - to conduct unique parallel searches using many nonlocally correlated search agents. The model is based on the property of a single-celled amoeba, the true slime mold Physarum, which maintains a constant intracellular resource volume while collecting environmental information by concurrently expanding and shrinking its branches. The conservation law entails a "nonlocal correlation" among the branches, i.e., volume increment in one branch is immediately compensated by volume decrement(s) in the other branch(es). This nonlocal correlation was shown to be useful for decision making in the case of a dilemma. The multi-armed bandit problem is to determine the optimal strategy for maximizing the total reward sum with incompatible demands. Our model can efficiently manage this "exploration-exploitation dilemma" and exhibits good performances. The average accuracy rate of our model is higher than those of well-known algorithms such as the modified ε-greedy algorithm and modified softmax algorithm.

Original languageEnglish
Title of host publicationUnconventional Computation - 9th International Conference, UC 2010, Proceedings
Pages69-80
Number of pages12
DOIs
Publication statusPublished - 2010 Dec 1
Externally publishedYes
Event9th International Conference on Unconventional Computation, UC 2010 - Tokyo, Japan
Duration: 2010 Jun 212010 Jun 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6079 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Unconventional Computation, UC 2010
CountryJapan
CityTokyo
Period10/6/2110/6/25

Keywords

  • Amoeba-based computing
  • Bio-inspired computation
  • Multi-armed bandit problem
  • Reinforcement learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Tug-of-war model for multi-armed bandit problem'. Together they form a unique fingerprint.

Cite this