Abstract
A grammar-guided genetic program is presented to automatically build and evolve populations of AI controlled enemies in a 2D third-person shooter called Genes of War. This evolutionary system constantly adapts enemy behaviour, encoded by a multi-layered fuzzy control system, while the game is being played. Thus the enemy behaviour fits a target challenge level for the purpose of maximizing player satisfaction. Two different methods to calculate this challenge level are presented: “hardwired” that allows the desired difficulty level to be programed at every stage of the gameplay, and “adaptive” that automatically determines difficulty by analyzing several features extracted from the player’s gameplay. Results show that the genetic program successfully adapts armies of ten enemies to different kinds of players and difficulty distributions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Azaria, Y., Sipper, M.: Gp-gammon: Using genetic programming to evolve backgammon players. Genetic Programming, 143–143 (2005)
Benbassat, A., Sipper, M.: Evolving board-game players with genetic programming. In: Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation, pp. 739–742. ACM (2011)
Couchet, J., Manrique, D., Ríos, J., Rodríguez-Patón, A.: Crossover and mutation operators for grammar-guided genetic programming. Soft Computing: A Fusion of Foundations, Methodologies and Applications 11(10), 943–955 (2007)
Doull, A.: The death of the level designer, http://roguelikedeveloper.blogspot.com/2008/01/death-of-level-designer-procedural.html (last accessed November 2011)
Font, J.M., Manrique, D., Pascua, E.: Grammar-Guided Evolutionary Construction of Bayesian Networks. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds.) IWINAC 2011, Part I. LNCS, vol. 6686, pp. 60–69. Springer, Heidelberg (2011)
Font, J.M., Manrique, D.: Grammar-guided evolutionary automatic system for autonomously building biological oscillators. In: 2010 IEEE Congress on Evolutionary Computation, pp. 1–7 (July 2010)
Font, J.M., Manrique, D., Ríos, J.: Evolutionary construction and adaptation of intelligent systems. Expert Systems with Applications 37, 7711–7720 (2010)
Hastings, E., Guha, R., Stanley, K.: Evolving content in the galactic arms race video game. In: IEEE Symposium on Computational Intelligence and Games, CIG 2009, pp. 241–248. IEEE (2009)
Loiacono, D., Cardamone, L., Lanzi, P.: Automatic track generation for high-end racing games using evolutionary computation. IEEE Transactions on Computational Intelligence and AI in Games 3(3), 245–259 (2011)
Lucas, S.: Computational intelligence and games: Challenges and opportunities. International Journal of Automation and Computing 5(1), 45–57 (2008)
Pedersen, C., Togelius, J., Yannakakis, G.: Modeling player experience in super mario bros. In: IEEE Symposium on Computational Intelligence and Games, CIG 2009, pp. 132–139. IEEE (2009)
Shichel, Y., Ziserman, E., Sipper, M.: Gp-robocode: Using genetic programming to evolve robocode players. Genetic Programming, 143–143 (2005)
Stanley, K., Bryant, B., Miikkulainen, R.: Real-time neuroevolution in the nero video game. IEEE Transactions on Evolutionary Computation 9(6), 653–668 (2005)
Togelius, J., De Nardi, R., Lucas, S.: Towards automatic personalised content creation for racing games. In: IEEE Symposium on Computational Intelligence and Games, CIG 2007, pp. 252–259. IEEE (2007)
Togelius, J., Whitehead, J., Bidarra, R.: Guest editorial: Procedural content generation in games. IEEE Transactions on Computational Intelligence and AI in Games 3, 169–171 (2011)
Togelius, J., Yannakakis, G., Stanley, K., Browne, C.: Search-Based Procedural Content Generation. In: Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcazar, A.I., Goh, C.-K., Merelo, J.J., Neri, F., Preuß, M., Togelius, J., Yannakakis, G.N. (eds.) EvoApplicatons 2010. LNCS, vol. 6024, pp. 141–150. Springer, Heidelberg (2010)
Yannakakis, G., Hallam, J.: Real-time game adaptation for optimizing player satisfaction. IEEE Transactions on Computational Intelligence and AI in Games 1(2), 121–133 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Font, J.M. (2012). Evolving Third-Person Shooter Enemies to Optimize Player Satisfaction in Real-Time. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2012. Lecture Notes in Computer Science, vol 7248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29178-4_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-29178-4_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29177-7
Online ISBN: 978-3-642-29178-4
eBook Packages: Computer ScienceComputer Science (R0)