Analyzing the effects of module encapsulation on search space bias

Modularity is thought to improve the evolvability of biological systems [18, 22]. Recent studies in the field of evolutionary computation show that the use of modularity improves performance and scalability of evolutionary algorithms for certain applications. [5, 12, 15, 16, 17]. The effects of introducing modularity to evolutionary search, however, are not well understood. This paper focuses on analyzing the effects of modularity on evolutionary computation. In particular, we analyze the effects of modular representations on the search space bias. Categories and Subject Descriptors I.2.4 [Artificial Intelligence]: Knowledge Representation Formalisms and Methods —Representations (procedural and rule-based); I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Heuristic methods General Terms Algorithms Keywords Modularity, Search Algorithms, Genetic Algorithms

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Ozlem O. Garibay, Annie S. Wu
• Keywords: Algorithms Keywords Modularity, Evolutionary Computation, GECCO 2007, Modularity Improves Performance