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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)
The problem of programming an artificial ant to follow the Santa Fe trail is used as an example program search space. Previously reported genetic programming, simulated annealing and hill climbing performance is shown not to be much better than random search on the Ant problem. Enumeration of a small fraction of the total search space and random sampling(More)