Memory with Memory in Tree-Based Genetic Programming

  • Authors:

  • Riccardo Poli;Nicholas F. Mcphee;Luca Citi;Ellery Crane

  • Affiliations:

  • School of Computer Science and Electronic Engineering, University of Essex, UK;Division of Science and Mathematics, University of Minnesota, Morris, USA;School of Computer Science and Electronic Engineering, University of Essex, UK;Division of Science and Mathematics, University of Minnesota, Morris, USA

  • Venue:
  • EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
  • Year:
  • 2009

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Abstract

In recent work on linear register-based genetic programming (GP) we introduced the notion of Memory-with-Memory (MwM), where the results of operations are stored in registers using a form of soft assignment which blends a result into the current content of a register rather than entirely replace it. The MwM system yielded very promising results on a set of symbolic regression problems. In this paper, we propose a way of introducing MwM style behaviour in tree-based GP systems. The technique requires only very minor modifications to existing code, and, therefore, is easy to apply. Experiments on a variety of synthetic and real-world problems show that MwM is very beneficial in tree-based GP, too.