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The latest book on Genetic Programming, Poli, Langdon and McPhee's (with contributions from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark with the authors choosing to make their work freely available by publishing using a form of the Creative Commons License[1]. In so doing they have created a must-read resource which(More)
— We use a form of grammar-based linear Genetic Programming (GP) as a hyperheuristic, i.e., a search heuristic on the space of heuristics. This technique is guided by domain-specific languages that one designs taking inspiration from elementary components of specialised heuristics and metaheuris-tics for a domain. We demonstrate this approach for(More)
Recommended by T. Blackwell Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimisation (PSO) and evolutionary algorithms. This connection enables us to generalise PSO to virtually any solution representation in a natural and straightforward way. The new geometric(More)
Evolutionary computation is a class of global search techniques based on the learning process of a population of potential solutions to a given problem, that has been successfully applied to a variety of problems. In this paper a new approach to the construction of neural networks based on evolutionary computation is presented. A linear chromosome combined(More)