Proofs and types
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Handbook of logic in computer science (vol. 2)
Strongly Typed Genetic Programming in Evolving Cooperation Strategies
Proceedings of the 6th International Conference on Genetic Algorithms
Towards a theory of type structure
Programming Symposium, Proceedings Colloque sur la Programmation
Performance-Enhanced Genetic Programming
EP '97 Proceedings of the 6th International Conference on Evolutionary Programming VI
An abstraction-based genetic programming system
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Strongly typed genetic programming
Evolutionary Computation
I/O guided detection of list catamorphisms: towards problem specific use of program templates in IP
Proceedings of the 2010 ACM SIGPLAN workshop on Partial evaluation and program manipulation
MT-CGP: mixed type cartesian genetic programming
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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This article introduces our new approach to program representation for genetic programming (GP). We replace the usual s-expression representation scheme by a strongly-typed abstraction-based representation scheme. This allows us to represent many typical computational structures by abstractions rather than by functions defined in the GP system's terminal set. The result is a generic GP system that is able to express programming structures such as recursion and data types without explicit definitions. We demonstrate the expressive power of this approach by evolving simple boolean programs without defining a set of terminals. We also evolve programs that exhibit recursive behavior without explicitly defining recursion specific syntax in the terminal set. In this article, we present our approach and experimental results.