Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Generative representations for evolutionary design automation
Generative representations for evolutionary design automation
Evolving encapsulated programs as shared grammars
Genetic Programming and Evolvable Machines
Designing an Evolutionary Strategizing Machine for Game Playing and Beyond
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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A streamlined, open-source implementation of Shared Grammar Evolution represents candidate solutions as grammars that can share production rules. It offers competitive search performance, while requiring little user-tuning of parameters. Uniquely, the system natively supports the memoization of return values computed during evaluation, which are stored with each rule and also shared between solutions. Significant improvements in evaluation time, up to 3.9-fold in one case, were observed when solving a set of classic GP problems - and even greater improvements can be expected for computation-intensive tasks. Additionally, the rule-based caching of intermediate representations, specifically of the terminal stack, was explored. It was shown to produce significant, although lesser speedups that were partly negated by computational overhead, but may be useful in dynamic and memory-bound tasks otherwise not amenable to memoization.