Abstract
Creating the behavior for non-player characters in video games is a complex task that requires the collaboration among programmers and game designers.
Usually game designers are only allowed to change certain parameters of the behavior, while programmers write new code whenever the behavior intended by designers cannot be achieved by just parameter tweaking. This becomes a time-consuming process that requires several iterations of designers testing the solution provided by programmers, followed by additional changes in the requirements that programmers must again re-implement.
In this paper, we present an approach for creating the behavior of non-player characters in video games that gives more power to the game designer by combining program by demonstration and behavior trees. Our approach is able to build some parts of a behavior tree with the observed data in a previous training phase.
Supported by the Spanish Ministry of Science and Education (TIN2014-55006-R).
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References
Rasmussen, J.: Are behavior trees a thing of the past (2016). http://www.gamasutra.com/blogs/JakobRasmussen/20160427/271188/Are_Behavior_Trees_a_Thing_of_the_Past.php
Isla, D.: Halo 3 - building a better battle. In: Game Developers Conference (2008)
Isla, D.: Handling complexity in the Halo 2 AI. In: Game Developers Conference (2005)
Sagredo-Olivenza, I., Gómez-Martín, M.A., González-Calero, P.A.: Supporting the collaboration between programmers and designers building game AI. In: Chorianopoulos, K., Divitini, M., Hauge, J.B., Jaccheri, L., Malaka, R. (eds.) ICEC 2015. LNCS, vol. 9353, pp. 496–501. Springer, Cham (2015). doi:10.1007/978-3-319-24589-8_46
Ontañón, S., Mishra, K., Sugandh, N., Ram, A.: On-line case-based planning. Comput. Intell. 26(1), 84–119 (2010)
Floyd, M.W., Esfandiari, B., Lam, K.: A case-based reasoning approach to imitating robocup players. In: Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, Florida, 15–17 May 2008, pp. 251–256. AAAI Press, Coconut Grove (2008)
Ontanón, S., Ram, A.: Case-based reasoning and user-generated artificial intelligence for real-time strategy games. In: González-Calero, P.A., Gómez-Martín, M.A. (eds.) Artificial Intelligence for Computer Games, pp. 103–124. Springer, New York (2011)
Rubin, J., Watson, I.D.: On combining decisions from multiple expert imitators for performance. In: IJCAI-11 (2011)
Jaidee, U., Muñoz-Avila, H., Aha, D.W.: Case-based goal-driven coordination of multiple learning agents. In: Delany, S.J., Ontañón, S. (eds.) ICCBR 2013. LNCS, vol. 7969, pp. 164–178. Springer, Heidelberg (2013). doi:10.1007/978-3-642-39056-2_12
Dereszynski, E.W., Hostetler, J., Fern, A., Dietterich, T.G., Hoang, T.T., Udarbe, M.: Learning probabilistic behavior models in real-time strategy games. In: AIIDE (2011)
Fernández-Ares, A., Mora, A., García-Sánchez, P., Castillo, P., Merelo, J.: Analysing the influence of the fitness function on genetically programmed bots for a real-time strategy game. Entertainment Comput. 18, 15–29 (2017)
Ortega, J., Shaker, N., Togelius, J., Yannakakis, G.N.: Imitating human playing styles in super mario bros. Entertainment Comput. 4(2), 93–104 (2013)
Spronck, P., Ponsen, M., Sprinkhuizen-Kuyper, I., Postma, E.: Adaptive game AI with dynamic scripting. Mach. Learn. 63(3), 217–248 (2006)
Floreano, D., Dürr, P., Mattiussi, C.: Neuroevolution: from architectures to learning. Evol. Intel. 1(1), 47–62 (2008)
Robertson, G., Watson, I.: Building behavior trees from observations in real-time strategy games. In: v Innovations in Intelligent SysTems and Applications (INISTA), pp. 1–7. IEEE (2015)
Flórez-Puga, G., Gómez-Martín, M.A., Gómez-Martín, P.P., Díaz-Agudo, B., González-Calero, P.A.: Query enabled behaviour trees. IEEE Trans. Comput. Intell. AI Games 1(4), 298–308 (2009)
Silverman, B.W., Jones, M.C.: E. Fix and J.L. Hodges (1951): an important contribution to nonparametric discriminant analysis and density estimation: commentary on fix and Hodges. Int. Stat. Rev./Revue Internationale de Statistique 57(3), 233–238 (1989)
Rosenblatt, F.: Principles of neurodynamics. Perceptrons and the theory of brain mechanisms. Technical report, DTIC Document (1961)
Bentley, J.L.: Multidimensional binary search trees used for associative searching. Commun. ACM 18(9), 509–517 (1975)
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Sagredo-Olivenza, I., Gómez-Martín, P.P., Gómez-Martín, M.A., González-Calero, P.A. (2017). Combining Neural Networks for Controlling Non-player Characters in Games. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2017. Lecture Notes in Computer Science(), vol 10306. Springer, Cham. https://doi.org/10.1007/978-3-319-59147-6_59
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