Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Linear-Graph GP - A New GP Structure
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
It's fate: a self-organising evolutionary algorithm
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
An adaptive evolutionary approach for real-time vehicle routing and dispatching
Computers and Operations Research
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A number of recent studies introduced meta-evolutionary strategies and successfully used them for solving problems in genetic programming. While individual results indicate possibilities of successes and failures (e.g., Kantschik, Dittrich et al., 1998, 1999), the emerging global picture suggests that the approach may have universal, domain-independent advantages over traditional methods. Trying to develop a general theoretical understanding of this concept, we use Price's theorem to define fitness at a meta-level and show with two simple case studies (two-dimensional optimization and the Eight puzzle) that the ideology based on Price's theorem can work at a meta-level in a similar manner for very different problems. Specifically, Pricean definition of fitness for reproductive operators appears to be practically useful and essential for performance and stability of a certain class of meta-evolutionary algorithms.