Adaptive Approaches Towards Better GA Performance in Dynamic Fitness Landscapes
نویسندگان
چکیده
منابع مشابه
Dynamic Fitness Landscapes
Genetic Algorithms (GAs) are typically thought to work on static fitness landscapes. In contrast, natural evolution works on fitness landscapes that change over evolutionary time as a result of co-evolution. Sexual selection and predator-prey evolution are examined as clear examples of phenomena that transform fitness landscapes. The concept of co-evolution is subsequently defined, before attem...
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We study self-replicating molecules under externally varying conditions. Changing conditions such as temperature variations and/or alterations in the environment’s resource composition lead to both non-constant replication and decay rates of the molecules. In general, therefore, molecular evolution takes place in a dynamic rather than a static fitness landscape. We incorporate dynamic replicati...
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ژورنال
عنوان ژورنال: DAIMI Report Series
سال: 1994
ISSN: 2245-9316,0105-8517
DOI: 10.7146/dpb.v23i487.6981