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European Conference on Genetic Programming

EuroGP 2016: Genetic Programming pp 133–148Cite as

A Genetic Programming Approach for the Traffic Signal Control Problem with Epigenetic Modifications

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9594))

Abstract

This paper presents a proof-of-concept for an Epigenetics-based modification of Genetic Programming (GP). The modification is tested with a traffic signal control problem under dynamic traffic conditions.

We describe the new algorithm and show first results. Experiments reveal that GP benefits from properties such as phenotype differentiation, memory consolidation within generations and environmentally-induced change in behavior provided by the epigenetic mechanism. The method can be extended to other dynamic environments.

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Author information

Authors and Affiliations

  1. Memorial University of Newfoundland, St. John’s, NL, A1B 3X5, Canada

    Esteban Ricalde & Wolfgang Banzhaf

Authors
  1. Esteban Ricalde
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  2. Wolfgang Banzhaf
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Corresponding author

Correspondence to Esteban Ricalde .

Editor information

Editors and Affiliations

  1. Dalhousie University, Halifax, Nova Scotia, Canada

    Malcolm I. Heywood

  2. University College Dublin, Dublin, Ireland

    James McDermott

  3. Universidade Nova de Lisboa, Lisboa, Portugal

    Mauro Castelli

  4. CIUSC Dept Informatics Engg, University of Coimbra, Coimbra, Portugal

    Ernesto Costa

  5. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

A Traffic Parameteres

A Traffic Parameteres

Traffic parameters included in the terminal set:

  • topStatus: Status of the north-south direction light of the current intersection (returns 0 if the light is red, 1 if the light is yellow, 2 if the light is green and 3 if the turn left right is on).

  • bottomStatus: Status of south-north direction light of the current intersection (same output configuration that topStatus).

  • leftStatus: Status of west-east direction light of the current intersection (same output configuration that topStatus).

  • rightStatus: Status of east-west direction light of the current intersection (same output configuration that topStatus).

  • verQueue: Sum of the number of vehicles stopped in the north-south direction and the number of vehicles stopped in the south-north direction in the current intersection.

  • horQueue: Sum of the number of vehicles stopped in the west-east direction and the number of vehicles stopped in the east-west direction of the current intersection.

  • 1stTopNeighborQueue: Number of vehicles stopped in the north-south direction of the first intersection in the north direction of the current crossing.

  • 1stBottomNeighborQueue: Number of vehicles stopped in the south-north direction of the first intersection in the south direction of the current crossing.

  • 1stLeftNeighborQueue: Number of vehicles stopped in the west-east direction of the first intersection in the west direction of the current crossing.

  • 1stRightNeighborQueue: Number of vehicles stopped in the east-west direction of the first intersection in the east direction of the current crossing.

  • 2ndTopNeighborQueue: Number of vehicles stopped in the north-south direction of the second intersection in the north direction of the current crossing.

  • 2ndBottomNeighborQueue: Number of vehicles stopped in the south-north direction of the second intersection in the south direction of the current crossing.

  • 2ndLeftNeighborQueue: Number of vehicles stopped in the west-east direction of the second intersection in the west direction of the current crossing.

  • 2ndRightNeighborQueue: Number of vehicles stopped in the east-west direction of the second intersection in the east direction of the current crossing.

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Ricalde, E., Banzhaf, W. (2016). A Genetic Programming Approach for the Traffic Signal Control Problem with Epigenetic Modifications. In: Heywood, M., McDermott, J., Castelli, M., Costa, E., Sim, K. (eds) Genetic Programming. EuroGP 2016. Lecture Notes in Computer Science(), vol 9594. Springer, Cham. https://doi.org/10.1007/978-3-319-30668-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-30668-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30667-4

  • Online ISBN: 978-3-319-30668-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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