{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T13:35:20Z","timestamp":1772717720538,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T00:00:00Z","timestamp":1629331200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T00:00:00Z","timestamp":1629331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100008812","name":"Defence Science and Technology Group","doi-asserted-by":"publisher","award":["8280"],"award-info":[{"award-number":["8280"]}],"id":[{"id":"10.13039\/501100008812","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann Oper Res"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>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.<\/jats:p>","DOI":"10.1007\/s10479-021-04225-7","type":"journal-article","created":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T10:08:21Z","timestamp":1629367701000},"page":"901-936","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Discovering optimal strategy in tactical combat scenarios through the evolution of behaviour trees"],"prefix":"10.1007","volume":"320","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8620-6779","authenticated-orcid":false,"given":"Martin","family":"Masek","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chiou Peng","family":"Lam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luke","family":"Kelly","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Wong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,8,19]]},"reference":[{"key":"4225_CR1","unstructured":"Baker, J. E. (1987). Reducing bias and inefficiency in the selection algorithm. In Proceedings of the second international conference on genetic algorithms (Vol. 206, pp. 14\u201321)."},{"key":"4225_CR2","doi-asserted-by":"publisher","unstructured":"Berthling-Hansen, G., Morch, E., L\u00f8vlid, R. A., & Gundersen, O. E. (2018). Automating behaviour tree generation for simulating troop movements (poster). In 2018 IEEE conference on cognitive and computational aspects of situation management (CogSIMA) (pp. 147\u2013153). IEEE. https:\/\/doi.org\/10.1109\/COGSIMA.2018.8423978.","DOI":"10.1109\/COGSIMA.2018.8423978"},{"key":"4225_CR3","unstructured":"Bowden, F. D., Pincombe, B. M., & Williams, P. B. (2015). Feasible scenario spaces: A new way of measuring capability impacts. MODSIM2015, 836\u2013842."},{"issue":"6","key":"4225_CR4","first-page":"67","volume":"75","author":"H Courtney","year":"1997","unstructured":"Courtney, H., Kirkland, J., & Viguerie, P. (1997). Strategy under uncertainty. Harvard Business Review, 75(6), 67\u201379.","journal-title":"Harvard Business Review"},{"key":"4225_CR5","doi-asserted-by":"crossref","unstructured":"Deb, K., Agrawal, S., Pratap, A., & Meyarivan, T. (2000). A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In International conference on parallel problem solving from nature (pp. 849\u2013858). Springer, Berlin, Heidelberg.","DOI":"10.1007\/3-540-45356-3_83"},{"key":"4225_CR6","unstructured":"Evensen, P., Stien, H., & Helge Bentsen, D. (2018). Modeling battle drills for computer-generated forces using behavior trees. In Interservice\/industry training, simulation, and education conference (I\/ITSEC), Orlando, Florida, November 2018."},{"key":"4225_CR7","doi-asserted-by":"crossref","unstructured":"Gajurel, A., Louis, S. J., M\u00e9ndez, D. J., & Liu, S. (2018). Neuroevolution for RTS micro. In 2018 IEEE conference on computational intelligence and games (CIG) (pp. 1\u20138). IEEE.","DOI":"10.1109\/CIG.2018.8490457"},{"key":"4225_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-020-03856-6","author":"S Gupta","year":"2021","unstructured":"Gupta, S., Modgil, S., Bhattacharyya, S., & Bose, I. (2021). Artificial intelligence for decision support systems in the field of operations research: Review and future scope of research. Annals of Operations Research. https:\/\/doi.org\/10.1007\/s10479-020-03856-6","journal-title":"Annals of Operations Research"},{"key":"4225_CR9","unstructured":"Hoff, J. W., & Christensen, H. J. (2016). Evolving Behaviour Trees:-Automatic Generation of AI Opponents for Real-Time Strategy Games (Master's thesis, NTNU)."},{"key":"4225_CR10","doi-asserted-by":"crossref","unstructured":"Hullett, K., & Whitehead, J. (2010). Design patterns in FPS levels. In Proceedings of the fifth international conference on the foundations of digital games (pp. 78\u201385). ACM.","DOI":"10.1145\/1822348.1822359"},{"key":"4225_CR11","unstructured":"Isla, D. (2005). Handling complexity in the Halo 2 AI, In Game developer conference 2005, international game developers association, San Francisco."},{"key":"4225_CR12","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.orp.2015.03.001","volume":"2","author":"AA Juan","year":"2015","unstructured":"Juan, A. A., Faulin, J., Grasman, S. E., Rabe, M., & Figueira, G. (2015). A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspectives, 2, 62\u201372.","journal-title":"Operations Research Perspectives"},{"key":"4225_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-021-04142-9","author":"AA Juan","year":"2021","unstructured":"Juan, A. A., Keenan, P., Mart\u00ed, R., McGarraghy, S., Panadero, J., Carroll, P., & Oliva, D. (2021). A review of the role of heuristics in stochastic optimisation: From metaheuristics to learnheuristics. Annals of Operations Research. https:\/\/doi.org\/10.1007\/s10479-021-04142-9","journal-title":"Annals of Operations Research"},{"key":"4225_CR14","doi-asserted-by":"crossref","unstructured":"Kocsis, L., & Szepesv\u00e1ri, C. (2006). Bandit based monte-carlo planning. In European conference on machine learning (pp. 282\u2013293). Springer, Berlin, Heidelberg.","DOI":"10.1007\/11871842_29"},{"key":"4225_CR15","volume-title":"Genetic programming: On the programming of computers by means of natural selection","author":"J Koza","year":"1992","unstructured":"Koza, J. (1992). Genetic programming: On the programming of computers by means of natural selection. MIT Press."},{"key":"4225_CR16","doi-asserted-by":"publisher","first-page":"100123","DOI":"10.1016\/j.orp.2019.100123","volume":"6","author":"CP Lam","year":"2019","unstructured":"Lam, C. P., Masek, M., Kelly, L., Papasimeon, M., & Benke, L. (2019). A simheuristic approach for evolving agent behaviour in the exploration for novel combat tactics. Operations Research Perspectives, 6, 100123.","journal-title":"Operations Research Perspectives"},{"key":"4225_CR17","doi-asserted-by":"publisher","unstructured":"Lim, C. U., Baumgarten, R., & Colton, S. (2010). Evolving behaviour trees for the commercial game DEFCON. In European conference on the applications of evolutionary computation (pp. 100\u2013110). Springer, Berlin, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-642-12239-2_11","DOI":"10.1007\/978-3-642-12239-2_11"},{"key":"4225_CR18","unstructured":"Masek, M., Lam, C. P., Kelly, L. & Wong, M. (2019). Evolving behaviour trees for automated discovery of novel combat strategy in real-time strategy wargames. In S. Elsawah (Ed.), MODSIM2019, 23rd international congress on modelling and simulation. Modelling and Simulation Society of Australia and New Zealand, December 2019, pp. 277\u2013283."},{"key":"4225_CR19","first-page":"58","volume":"2013","author":"S Onta\u00f1\u00f3n","year":"2013","unstructured":"Onta\u00f1\u00f3n, S. (2013). The combinatorial multi-armed bandit problem and its application to real-time strategy games. AIIDE, 2013, 58\u201364.","journal-title":"AIIDE"},{"issue":"4","key":"4225_CR20","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1109\/TCIAIG.2013.2286295","volume":"5","author":"S Ontan\u00f3n","year":"2013","unstructured":"Ontan\u00f3n, S., Synnaeve, G., Uriarte, A., Richoux, F., Churchill, D., & Preuss, M. (2013). A survey of real-time strategy game AI research and competition in starcraft. IEEE Transactions on Computational Intelligence and AI in Games, 5(4), 293\u2013311. https:\/\/doi.org\/10.1109\/TCIAIG.2013.2286295","journal-title":"IEEE Transactions on Computational Intelligence and AI in Games"},{"key":"4225_CR21","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1007\/BF02125421","volume":"63","author":"IH Osman","year":"1996","unstructured":"Osman, I. H., & Laporte, G. (1996). Metaheuristics: A bibliography. Annals of Operations Research, 63, 511\u2013623. https:\/\/doi.org\/10.1007\/BF02125421","journal-title":"Annals of Operations Research"},{"key":"4225_CR22","doi-asserted-by":"publisher","unstructured":"Perez, D., Nicolau, M., O\u2019Neill, M., & Brabazon, A. (2011). Reactiveness and navigation in computer games: Different needs, different approaches. In Paper presented at the 2011 IEEE conference on computational intelligence and games (CIG\u201911), Seoul, South Korea, August 31st-September 3rd 2011. (pp. 273\u2013280) IEEE. https:\/\/doi.org\/10.1109\/CIG.2011.6032017","DOI":"10.1109\/CIG.2011.6032017"},{"issue":"4","key":"4225_CR23","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1609\/aimag.v35i4.2478","volume":"35","author":"G Robertson","year":"2014","unstructured":"Robertson, G., & Watson, I. (2014). A review of real-time strategy game AI. AI Magazine, 35(4), 75\u2013104. https:\/\/doi.org\/10.1609\/aimag.v35i4.2478","journal-title":"AI Magazine"},{"key":"4225_CR24","doi-asserted-by":"publisher","unstructured":"Robertson, G., & Watson, I. (2015). Building behavior trees from observations in real-time strategy games. In 2015 International symposium on innovations in intelligent systems and applications (INISTA) https:\/\/doi.org\/10.1109\/INISTA.2015.7276774","DOI":"10.1109\/INISTA.2015.7276774"},{"key":"4225_CR25","doi-asserted-by":"crossref","unstructured":"Togelius, J., Karakovskiy, S., Koutn\u00edk, J., & Schmidhuber, J. (2009). Super mario evolution. In 2009 IEEE symposium on computational intelligence and games (pp. 156\u2013161). IEEE.","DOI":"10.1109\/CIG.2009.5286481"},{"issue":"7782","key":"4225_CR26","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1038\/s41586-019-1724-z","volume":"575","author":"O Vinyals","year":"2019","unstructured":"Vinyals, O., Babuschkin, I., Czarnecki, W. M., Mathieu, M., Dudzik, A., Chung, J., Choi, D. H., Powell, R., Ewalds, T., Georgiev, P., Junhyuk, O., Horgan, D., Kroiss, M., Danihelka, I., Huang, A., Sifre, L., Cai, T., Agapiou, J. P., Jaderberg, M., \u2026 Silver, D. (2019). Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature, 575(7782), 350\u2013354. https:\/\/doi.org\/10.1038\/s41586-019-1724-z","journal-title":"Nature"}],"container-title":["Annals of Operations Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-021-04225-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10479-021-04225-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-021-04225-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T11:25:44Z","timestamp":1673436344000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10479-021-04225-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,19]]},"references-count":26,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["4225"],"URL":"https:\/\/doi.org\/10.1007\/s10479-021-04225-7","relation":{},"ISSN":["0254-5330","1572-9338"],"issn-type":[{"value":"0254-5330","type":"print"},{"value":"1572-9338","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,19]]},"assertion":[{"value":"30 July 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no conflict of interest \/ competing interests to report.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The project does not include human or animal participants\u2014it was approved through the Edith Cowan University Ethics Declaration Process.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not Applicable\u2014no human or animal participants were used in this work.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not Applicable\u2014no human or animal participants were used in this work.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}