Evolutionary and lifetime learning in varying NK fitness landscape changing environments: An analysis of both fitness and diversity

Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

2 Citations (Scopus)

Abstract

This paper examines the effects of lifetime learning on populations evolving genetically in a series of changing environments. The analysis of both fitness and diversity of the populations provides an insight into the improved performance provided by lifetime learning. The NK fitness landscape model is employed as the problem task, which has the advantage of being able to generate a variety of fitness landscapes of varying difficulty. Experiments observe the response of populations in an environment where problem difficulty increases and decreases with varying frequency. Results show that lifetime learning is capable of overall higher fitness levels and, in addition, that lifetime learning stimulates the diversity of the population. This increased diversity allows lifetime learning a greater level of recovery and stability than evolutionary learning alone.

Original languageEnglish
Title of host publicationAAAI-07/IAAI-07 Proceedings
Subtitle of host publication22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Pages706-711
Number of pages6
Publication statusPublished - 2007
EventAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference - Vancouver, BC, Canada
Duration: 22 Jul 200726 Jul 2007

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume1

Conference

ConferenceAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Country/TerritoryCanada
CityVancouver, BC
Period22/07/0726/07/07

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