Memory analysis and significance test for agent behaviours

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

3 Citations (Scopus)

Abstract

Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper, we handle the artificial ant problem, an agent task to model ant trail following in a grid world, which is one of the difficult problems that purely reactive systems cannot solve. We provide an evolutionary approach to quantify the amount of memory needed for the agent problem and explore a systematic analysis over the memory usage. We apply two types of memory-based control structures, Koza's genetic programming and finite state machines, to recognize the relevance of internal memory. Statistical significance test based on beta distribution differentiates the characteristics and performances of the two control structures.

Original languageEnglish
Title of host publicationGECCO 2006 - Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery (ACM)
Pages151-158
Number of pages8
ISBN (Print)1595931864, 9781595931863
DOIs
Publication statusPublished - 2006
Event8th Annual Genetic and Evolutionary Computation Conference 2006 - Seattle, WA, United States
Duration: 2006 Jul 82006 Jul 12

Publication series

NameGECCO 2006 - Genetic and Evolutionary Computation Conference
Volume1

Other

Other8th Annual Genetic and Evolutionary Computation Conference 2006
CountryUnited States
CitySeattle, WA
Period06/7/806/7/12

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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    Kim, D. E. (2006). Memory analysis and significance test for agent behaviours. In GECCO 2006 - Genetic and Evolutionary Computation Conference (pp. 151-158). (GECCO 2006 - Genetic and Evolutionary Computation Conference; Vol. 1). Association for Computing Machinery (ACM). https://doi.org/10.1145/1143997.1144025