Tag-based Module Regulation for Genetic Programming

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Date July 19th, 2022
DOI 10.1145/3520304.3534060
Venue The Genetic and Evolutionary Computation Conference

This Hot-off-the-Press paper summarizes our recently published work, “Tag-based regulation of modules in genetic programming improves context-dependent problem solving,” published in Genetic Programming and Evolvable Machines [1]. We introduce and experimentally demonstrate tag-based genetic regulation, a genetic programming (GP) technique that allows programs to dynamically adjust which code modules to express. Tags are evolvable labels that provide a flexible naming scheme for referencing code modules. Tag-based regulation extends tag-based naming schemes to allow programs to “promote” and “repress” code modules to alter module execution patterns. We find that tag-based regulation improves problem-solving success on problems where programs must adjust how they respond to current inputs based on prior inputs; indeed, some of these problems could not be solved until regulation was added. We also identify scenarios where the correct response to an input does not change over time, rendering tag-based regulation an unnecessary functionality that can sometimes impede evolution. Broadly, tag-based regulation adds to our repertoire of techniques for evolving more dynamic computer programs and can easily be incorporated into existing tag-enabled GP systems.

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  author = {Lalenini, Alexander and Moreno, Matthew Andres and Ofria, Charles},
  title = {Tag-based Module Regulation for Genetic Programming},
  year = {2022},
  isbn = {9781450392686},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3520304.3534060},
  doi = {10.1145/3520304.3534060},
  booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion},
  pages = {25-26},
  numpages = {2},
  keywords = {gene regulation, genetic programming, SignalGP, automatic program synthesis, tag-based referencing},
  location = {Boston, Massachusetts},
  series = {GECCO '22}
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Alexander Lalejini, Matthew Andres Moreno, and Charles Ofria. 2022. Tag-based Module Regulation for Genetic Programming. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO ‘22). Association for Computing Machinery, New York, NY, USA, 25–26. https://doi.org/10.1145/3520304.3534060

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