Abstract
The creation of believable characters is one of the most challenging problems in the interactive entertainment industry. Although there are different tools available for designers and programmers to define the behavior of non-player characters, it remains a complex and error prone process that requires a high level of technical knowledge. Learning from Demonstration is a promising field that studies how to build intelligent agents that are able to replicate behaviors, learning from demonstration of human experts. This approach is interesting for developers who do not have a computer science background, alleviating the need of representing tasks and knowledge in a formal way. In this work we present an online and case-based reasoning agent that learns how to imitate real players of Pac-Man using an interactive approach in which both the human player and the computational agent take turns controlling the main character. In our previous work, the agent was in complete control of the learning process so it decided when to give up or regain control of the character. Now the system have been improved so the player can also regain control of the character and go back in time to correct improper behaviors manifested by the agent whenever they are detected. We also present an evaluation of the system performed by three professional video game designers, followed by the main insights we have gained.
This work has been partially supported by the Spanish Committee of Economy and Competitiveness (TIN2017-87330-R) and the UCM (Group 921330).
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Notes
- 1.
Unity, https://unity.com.
- 2.
Unreal Engine, https://www.unrealengine.com.
References
Colledanchise, M., Ögren, P.: Behavior trees in robotics and AI: an introduction (2017)
Floyd, M.W., Davoust, A., Esfandiari, B.: Considerations for real-time spatially-aware case-based reasoning: a case study in robotic soccer imitation. In: Althoff, K.-D., Bergmann, R., Minor, M., Hanft, A. (eds.) ECCBR 2008. LNCS (LNAI), vol. 5239, pp. 195–209. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85502-6_13
Floyd, M.W., Esfandiari, B.: An active approach to automatic case generation. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS (LNAI), vol. 5650, pp. 150–164. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02998-1_12
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, 15–17 May, 2008, Coconut Grove, Florida, USA, pp. 251–256 (2008)
Geisler, B.: An empirical study of machine learning algorithms applied to modeling player behavior in a “first person shooter” video game. Ph.D. thesis, Citeseer (2002)
Hingston, P.: A new design for a turing test for bots. In: Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, CIG 2010, Copenhagen, Denmark, 18–21 August, 2010, pp. 345–350 (2010)
Daumé, H., Langford, J., Marcu, D.: Search-based structured prediction. Mach. Learn. 75(3), 297–325 (2009)
Lam, K., Esfandiari, B., Tudino, D.: A scene-based imitation framework for RoboCup clients. MOO-Modeling Other Agents from Observations (2006)
Lamontagne, L., Rugamba, F., Mineau, G.: Acquisition of cases in sequential games using conditional entropy. In: ICCBR 2012 Workshop on TRUE: Traces for Reusing Users’ Experience (2012)
Miranda, M., Sánchez-Ruiz, A.A., Peinado, F.: A CBR approach for imitating human playing style in Ms. Pac-Man video game. In: Cox, M.T., Funk, P., Begum, S. (eds.) ICCBR 2018. LNCS (LNAI), vol. 11156, pp. 292–308. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01081-2_20
Miranda, M., Sánchez-Ruiz, A.A., Peinado, F.: Towards human-like bots using online interactive case-based reasoning. In: Bach, K., Marling, C. (eds.) ICCBR 2019. LNCS (LNAI), vol. 11680, pp. 314–328. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29249-2_21
Ortega, J., Shaker, N., Togelius, J., Yannakakis, G.N.: Imitating human playing styles in super mario bros. Entertain. Comput. 4(2), 93–104 (2013)
Packard, B., Ontañón, S.: Policies for active learning from demonstration. In: 2017 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 27–29, 2017 (2017)
Packard, B., Ontañón, S.: Learning behavior from limited demonstrations in the context of games. In: Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018, Melbourne, Florida, USA, May 21–23, 2018, pp. 86–91 (2018)
Rohlfshagen, P., Liu, J., Pérez-Liébana, D., Lucas, S.M.: Pac-Man conquers academia: two decades of research using a classic arcade game. IEEE Trans. Games 10, 233–256 (2018)
Ross, S., Bagnell, D.: Efficient reductions for imitation learning. In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Sardinia, Italy, May 13–15, 2010, pp. 661–668 (2010)
Ross, S., Gordon, G.J., Bagnell, D.: A reduction of imitation learning and structured prediction to no-regret online learning. In: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2011, Fort Lauderdale, USA, April 11–13, 2011, pp. 627–635 (2011)
Soni, B., Hingston, P.: Bots trained to play like a human are more fun. In: 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), pp. 363–369 (2008)
Togelius, J., Nardi, R.D., Lucas, S.M.: Towards automatic personalised content creation for racing games. In: 2007 IEEE Symposium on Computational Intelligence and Games, pp. 252–259 (2007)
Williams, P.R., Liebana, D.P., Lucas, S.M.: Ms. Pac-Man versus ghost team CIG 2016 competition. In: IEEE Conference on Computational Intelligence and Games, CIG 2016, Santorini, Greece, September 20–23, 2016, pp. 1–8 (2016)
Wooldridge, M.: Introduction to multiagent systems. Cell 757(239), 8573 (2002)
Yannakakis, G.N., Maragoudakis, M.: Player modeling impact on player’s entertainment in computer games. In: Ardissono, L., Brna, P., Mitrovic, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 74–78. Springer, Heidelberg (2005). https://doi.org/10.1007/11527886_11
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Miranda, M., Sánchez-Ruiz, A.A., Peinado, F. (2020). Building Non-player Character Behaviors By Imitation Using Interactive Case-Based Reasoning. In: Watson, I., Weber, R. (eds) Case-Based Reasoning Research and Development. ICCBR 2020. Lecture Notes in Computer Science(), vol 12311. Springer, Cham. https://doi.org/10.1007/978-3-030-58342-2_17
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