Neutrality and gradualism: encouraging exploration and exploitation simultaneously with Binary Decision Diagrams

Search algorithms are subject to the trappings of local optima. Attempts to address the problem are often framed in the context of needing to balance, or trade-off, exploitation against exploration. Ideally, it is best to maximise both simultaneously, but this is usually seen as infeasible in the pr...

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Bibliographic Details
Published in2006 IEEE International Conference on Evolutionary Computation pp. 615 - 622
Main Author Downing, R.M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2006
Subjects
Algorithm design and analysis
Boolean functions
Computer science
Costs
Data structures
Evolutionary computation
Genetic mutations
Genetic programming
Testing
Uncertainty
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ISBN9780780394872
0780394879
ISSN1089-778X
DOI10.1109/CEC.2006.1688367

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Summary:Search algorithms are subject to the trappings of local optima. Attempts to address the problem are often framed in the context of needing to balance, or trade-off, exploitation against exploration. Ideally, it is best to maximise both simultaneously, but this is usually seen as infeasible in the presence of multi-modal search spaces. This paper investigates the potential for exploration of both neutrality and mutation rate, and argues that the former is the more important. The most interesting result, however, is that the necessity for a trade-off between exploitation and exploration can be avoided within the context of our algorithm for evolving binary decision diagrams.
ISBN:9780780394872
0780394879
ISSN:1089-778X
DOI:10.1109/CEC.2006.1688367