ORCID : 0000-0001-8620-6779
ORCID : 0000-0002-4843-9229
Annals of Operations Research
School of Science
Edith Cowan University - Open Access Support Scheme 2021
Defence Science and Technology Group, Australia
In this paper we address the problem of automatically discovering optimal tactics in a combat scenario in which two opposing sides control a number of fighting units. Our approach is based on the evolution of behaviour trees, combined with simulation-based evaluation of solutions to drive the evolution. Our behaviour trees use a small set of possible actions that can be assigned to a combat unit, along with standard behaviour tree constructs and a novel approach for selecting which action from the tree is performed. A set of test scenarios was designed for which an optimal strategy is known from the literature. These scenarios were used to explore and evaluate our approach. The results indicate that it is possible, from the small set of possible unit actions, for a complex strategy to emerge through evolution. Combat units with different capabilities were observed exhibiting coordinated team work and exploiting aspects of the environment.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Securing Digital Futures
Artificial intelligence and autonomous systems