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Genetic Programming Theory and Practice XIX pp 57–79Cite as

GUI-Based, Efficient Genetic Programming and AI Planning for Unity3D

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Part of the book series: Genetic and Evolutionary Computation ((GEVO))

Abstract

We present a GUI-driven and efficient Genetic Programming (GP) and AI Planning framework designed for agent-based learning research. Our framework, ABL-Unity3D, is built in Unity3D, a game development environment. ABL-Unity3D addresses challenges entailed in co-opting Unity3D: making the simulator serve agent learning rather than humans playing a game, lowering fitness evaluation time to make learning computationally feasible, and interfacing GP with an AI Planner to support hybrid algorithms. We achieve this by developing a Graphical User Interface (GUI) using the Unity3D editor’s programmable interface and performance optimizations. These optimizations result in at least a 3x speedup. In addition, we describe ABL-Unity3D by explaining how to use it for an example experiment using GP and AI Planning. We benchmark ABL-Unity3D by measuring the performance and speed of the AI Planner alone, GP alone, and the AI Planner with GP.

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Acknowledgments

This research was, in part, funded by the U.S. Government. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.

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Authors and Affiliations

  1. ALFA, MIT CSAIL, Cambridge, MA, USA

    Robert Gold, Andrew Haydn Grant, Erik Hemberg, Chathika Gunaratne & Una-May O’Reilly

Authors
  1. Robert Gold
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  2. Andrew Haydn Grant
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  3. Erik Hemberg
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  4. Chathika Gunaratne
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  5. Una-May O’Reilly
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Corresponding author

Correspondence to Robert Gold .

Editor information

Editors and Affiliations

  1. Engineering Sciences Graduate Program, Tecnológico Nacional de México/Instituto Tecnológico de Tijuana, Tijuana, Baja California, Mexico

    Leonardo Trujillo

  2. Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Wels, Austria

    Stephan M. Winkler

  3. Department of Informatics, Faculty of Sciences, University of Lisbon, Lisbon, Portugal

    Sara Silva

  4. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Wolfgang Banzhaf

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Gold, R., Grant, A.H., Hemberg, E., Gunaratne, C., O’Reilly, UM. (2023). GUI-Based, Efficient Genetic Programming and AI Planning for Unity3D. In: Trujillo, L., Winkler, S.M., Silva, S., Banzhaf, W. (eds) Genetic Programming Theory and Practice XIX. Genetic and Evolutionary Computation. Springer, Singapore. https://doi.org/10.1007/978-981-19-8460-0_3

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  • DOI: https://doi.org/10.1007/978-981-19-8460-0_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-8459-4

  • Online ISBN: 978-981-19-8460-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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