Abstract
Behaviour trees offer a means to systematically decompose a behaviour into a set of steps within a tree structure. Genetic programming, which has at its core the evolution of tree-like structures, thus presents an ideal tool to identify novel behaviour patterns that emerge when the algorithm is guided by a set fitness function. In this paper, we present our framework for novel behaviour discovery using evolved behaviour trees, with some examples from the beyond-visual range air combat domain where distinct strategies emerge in response to modelling the effects of electronic warfare.
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Acknowledgements
The authors would like to acknowledge the work of Richard Brain and Lilia Finkelshtein for work on the ACE 2 Simulation environment and hand-design of an opponent behaviour tree to drive evaluation. This research is supported by the Defence Science and Technology Group, Australia under the Modelling Complex Warfighting Strategic Research Investment. The authors would also like to acknowledge the support of Mr. Martin Cross (DST) who sponsored this research.
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Masek, M., Lam, C.P., Kelly, L., Benke, L., Papasimeon, M. (2021). A Genetic Programming Framework for Novel Behaviour Discovery in Air Combat Scenarios. In: Ernst, A.T., Dunstall, S., GarcÃa-Flores, R., Grobler, M., Marlow, D. (eds) Data and Decision Sciences in Action 2. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-60135-5_19
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DOI: https://doi.org/10.1007/978-3-030-60135-5_19
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