Learning the Ideal Evaluation Function Export

@incollection{citeulike:2857388, abstract = {Designing an adequate fitness function requires substantial knowledge of a problem and of features that indicate progress towards a solution. Coevolution takes the human out of the loop by dynamically constructing the evaluation function based on interactions between evolving individuals. A question is to what extent such automatic evaluation can be adequate. We define the notion of an ideal evaluation function. It is shown that coevolution can in principle achieve ideal evaluation. Moreover, progress towards ideal evaluation can be measured. This observation leads to an algorithm for coevolution. The algorithm makes stable progress on several challenging abstract test problems.}, author = {de Jong, Edwin and Pollack, Jordan}, citeulike-article-id = {2857388}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/3-540-45105-6_34}, doi = {10.1007/3-540-45105-6_34}, journal = {Genetic and Evolutionary Computation — GECCO 2003}, keywords = {coevolution, evolution, ga, gp}, pages = {203}, posted-at = {2008-06-27 18:11:54}, priority = {2}, title = {Learning the Ideal Evaluation Function}, url = {http://dx.doi.org/10.1007/3-540-45105-6_34}, year = {2003} }

TY - CHAP ID - citeulike:2857388 L3 - citeulike-article-id:2857388 N2 - Designing an adequate fitness function requires substantial knowledge of a problem and of features that indicate progress towards a solution. Coevolution takes the human out of the loop by dynamically constructing the evaluation function based on interactions between evolving individuals. A question is to what extent such automatic evaluation can be adequate. We define the notion of an ideal evaluation function. It is shown that coevolution can in principle achieve ideal evaluation. Moreover, progress towards ideal evaluation can be measured. This observation leads to an algorithm for coevolution. The algorithm makes stable progress on several challenging abstract test problems. JF - Genetic and Evolutionary Computation — GECCO 2003 EP - 203 TI - Learning the Ideal Evaluation Function SP - 203 KW - coevolution KW - evolution KW - ga KW - gp AU - de Jong, Edwin AU - Pollack, Jordan PY - 2003/// UR - http://dx.doi.org/10.1007/3-540-45105-6_34 ER -