Title

A genetic programming framework for novel behaviour discovery in air combat scenarios

Document Type

Conference Proceeding

Publication Title

Data and Decision Sciences in Action 2

Publisher

Springer

School

School of Science

RAS ID

32941

Comments

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 Data and Decision Sciences in Action 2 (pp. 263-277). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-030-60135-5_19

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.

DOI

10.1007/978-3-030-60135-5

Access Rights

subscription content

Research Themes

Securing Digital Futures

Priority Areas

Artificial intelligence and autonomous systems

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