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Symbiotic Composition Watson & Pollack Summarized by KC Tsui
Motivations • Evolutionary Transition: symbiogenic origin of eukaryotes from proharyotes • Improvement in performance by EA (operators) gets more difficult as the ‘evolution’ progresses • Symbiotic composition • pre-adaptation of sets of features • Entities become components of composite entities at a higher level of organization (cf. AOC)
SEAM • Symbiogenic Evolutionary Adaptation Model • population of entities: an ecosystem of different species • variation operator: a means for joining two entities in a symbiotic union • fitness • how stable is a union? • overall fitness is a function of many context sensitive fitness • Environment context: the biotic environment provided by other coevolving entities
SEAM (cont.) Create many different small entities While not end join a pair of entities (symbiotic composition) evaluate if resultant dominates the constituents in the current context keep else break end-if End-while
Symbiotic Composition A: --0---0----1---- B: 1-------01----0- A+B: 1-0---0-01-1--0- A: ----1----00-1-- B: --1-0---0-1---- A+B: --1-1---000-1-- ‘incomplete’ entities are created!
Fitness Evaluation • Overall fitness is a weighted sum of context sensitive fitness • Pareto dominance is used to determine stability • Context is formed by combining features of other entities in the current population
Hierarchical-if-and-only-if (HIFF) landscape • a hierarchically clustered structure • Starts with a two-feature epistasis model • Continue (recursively) adding other epistasis models • Analogous to an recursive prisoners’ dilemma • HIFF representative of self-organized dynamic systems – with ‘power law’ signatures
Questions • Is HIFF generic enough to capture many problems such as TSP? • How different is it from COEA? • Reference • Watson & Pollack, A Computational Model of Symbiotic Composition in Evolutionary Transitions, to appear in Biosystems Journal, 2002 (http://www.demo.cs.brandeis.edu/papers/long.html#biosystems_scet)