031407 - Lecture 15 Recall Done with evolution strategies(1...

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Lecture 15: 03/14/2007 Recall: Done with evolution strategies. ((1+1)-ES, (μ+λ)-ES, (μ,λ)-ES) Wrap up the EP + ES discussion: 1. EP a. Constant size populations b. Mutation as only source of genetic randomness c. Selection process is deterministic (no “selective randomness”) d. Individuals in the populations were not mutually isomorphic e. Goal: AI-oriented 2. ES a. Also constant-sized populations (μ) b. Early (and bulk of later) work: mutation as only source of genetic randomness; later, some work using recombination of various kinds. c. Deterministic selection process, again d. Isomorphic individuals (vectors in R n ) e. Goal: maximize f(x) over x f. Also, in EP, “environment” is changing (sequence segments you want to match get longer); where as in ES it’s static On to genetic algorithms (GA)-invented in ‘60s, ‘70s by John Holland at U. Michigan-CS. Big picture : A set φ of “candidate problem solutions” and a f: φ ->R called a fitness function , exogenously (ie, from the outside) specified ahead of time. “f(φ 1 )>f(φ 2 )” <-> “φ 1 is a better problem solution than φ 2 Also have a set G of “genotypes” and a surjective mapping: g:G->
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  • Spring '07
  • Algorithms, current population, Constant size populations, genetic randomness, Deterministic selection process, bitwise mutation probability

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