Evolving content in the galactic arms race video game

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Hastings, E.J., Guha, R.K., Stanley, K.O.: Evolving content in the galactic arms race video game. In: Proceedings of the IEEE Symposium on Computational Intelligence and Games (CIG 2009), pp. 241–248. IEEE (2009)




Video game content includes the levels, models, items, weapons, and other objects encountered and wielded by players during the game. In most modern video games, the set of content shipped with the game is static and unchanging, or at best, randomized within a narrow set of parameters. However, ideally, if game content could be constantly renewed, players would remain engaged longer in the evolving stream of novel content. To realize this ambition, this paper introduces the content-generating neuroevolution of augmenting topologies (cgNEAT) algorithm, which automatically evolves game content based on player preferences, as the game is played. To demonstrate this approach, the galactic arms race (GAR) video game is also introduced. In GAR, players pilot space ships and fight enemies to acquire unique particle system weapons that are evolved by the game. As shown in this paper, players can discover a wide variety of content that is not only novel, but also based on and extended from previous content that they preferred in the past. The implication is that it is now possible to create games that generate their own content to satisfy players, potentially significantly reducing the cost of content creation and increasing the replay value of games.

Extended Abstract


author={E. J. Hastings and R. K. Guha and K. O. Stanley},
booktitle={2009 IEEE Symposium on Computational Intelligence and Games},
title={Evolving content in the Galactic Arms Race video game},
keywords={computer games;human computer interaction;video signal processing;augmenting topologies algorithm;content-generating neuroevolution;galactic arms race video game;particle system weapons;Arm;Artificial neural networks;Costs;Evolutionary computation;Games;Machine learning;Marine vehicles;Streaming media;Topology;Weapons},
url={http://dx.doi.org/10.1109/CIG.2009.5286468 http://de.evo-art.org/index.php?title=Evolving_content_in_the_galactic_arms_race_video_game},

Used References

R. Edwards, "The economics of game publishing," IGN Entertainment, 2006. [Online]. Available: http://games.ign.com/articles/708/708972p1.html

M. J. Irwin, "Game developers' trade off," Forbes.com, 2008. [Online]. Available: http://www.forbes.com/2008/05/27/videogame-art-money-tech-personal-cxmji0528vgames.html

V. Software, "Source engine SDK," 2007. [Online]. Available: http://developer.valvesoftware.com

E. Games, "Unreal engine SDK," 2007. [Online]. Available: http://www.unrealtechnology.com/

K. O. Stanley, B. D. Bryant, and R. Miikkulainen, "Real-time neuroevolution in the NERO video game," IEEE Transactions on Evolutionary Computation Special Issue on Evolutionary Computation and Games, vol. 9, no. 6, pp. 653-668, 2005. http://dx.doi.org/10.1109/TEVC.2005.856210

J. Togelius, R. D. Nardi, and S. M. Lucas, "Towards automatic personalised content creation for racing games," in Proceedings of the IEEE Symposium on Computational Intelligence and Games, 2007.

-, "An experiment in automatic game design," in Proceedings of the IEEE Symposium on Computational Intelligence and Games, 2008. http://dx.doi.org/10.1109/CIG.2008.5035629

F. Gomez and R. Miikkulainen, "Solving non-Markovian control tasks with neuroevolution," in Proceedings of the 16th International Joint Conference on Artificial Intelligence. San Francisco: Kaufmann, 1999, pp. 1356-1361.

N. Saravanan and D. B. Fogel, "Evolving neural control systems," IEEE Expert, pp. 23-27, June 1995. http://dx.doi.org/10.1109/64.393139

F. Gruau, D. Whitley, and L. Pyeatt, "A comparison between cellular encoding and direct encoding for genetic neural networks," in Genetic Programming 1996: Proceedings of the First Annual Conference, J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, Eds. Cambridge, MA: MIT Press, 1996, pp. 81-89.

B.-T. Zhang and H. Muhlenbein, "Evolving optimal neural networks using genetic algorithms with Occam's razor," CplxSys, vol. 7, pp. 199-220, 1993.

X. Yao, "Evolving artificial neural networks," Proceedings of the IEEE, vol. 87, no. 9, pp. 1423-1447, 1999. http://dx.doi.org/10.1109/5.784219

A. P. Martin, "Increasing genomic complexity by gene duplication and the origin of vertebrates," The American Naturalist, vol. 154, no. 2, pp. 111-128, 1999. http://dx.doi.org/10.1086/303231

J. D. Watson, N. H. Hopkins, J. W. Roberts, J. A. Steitz, and A. M. Weiner, Molecular Biology of the Gene Fourth Edition. Menlo Park, CA: The Benjamin Cummings Publishing Company, Inc., 1987.

L. Altenberg, "Evolving better representations through selective genome growth," in Proceedings of the IEEE World Congress on Computational Intelligence. Piscataway, NJ: IEEE Press, 1994, pp. 182-187. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=350019&navigation=1

I. Harvey, "The artificial evolution of adaptive behavior," Ph.D. dissertation, School of Cognitive and Computing Sciences, University of Sussex, Sussex, 1993.

K. O. Stanley and R. Miikkulainen, "Evolving neural networks through augmenting topologies," Evolutionary Computation, vol. 10, pp. 99-127, 2002. http://dx.doi.org/10.1162/106365602320169811

M. E. Taylor, S. Whiteson, and P. Stone, "Comparing evolutionary and temporal difference methods in a reinforcement learning domain," in GECCO 2006: Proceedings of the Genetic and Evolutionary Computation Conference, July 2006, pp. 1321-1328. http://dx.doi.org/10.1145/1143997.1144202

J. Secretan, N. Beato, D. B. D'Ambrosio, A. Rodriguez, A. Campbell, and K. O. Stanley, "Picbreeder: Evolving pictures collaboratively online," in Proceedings of the Computer Human Interaction Conference, 2008. http://dx.doi.org/10.1145/1357054.1357328

T. Aaltonen et al., "Measurement of the top quark mass with dilepton events selected using neuroevolution at CDF," Physical Review Letters, 2009, to appear. http://dx.doi.org/10.1103/PhysRevLett.102.152001

K. O. Stanley, "Exploiting regularity without development," in Proceedings of the AAAI Fall Symposium on Developmental Systems. Menlo Park, CA: AAAI Press, 2006.

-, "Compositional pattern producing networks: A novel abstraction of development," Genetic Programming and Evolvable Machines Special Issue on Developmental Systems, pp. 131 - 162, 2007. http://dx.doi.org/10.1007/s10710-007-9028-8

A. Hoover, , and K. O. Stanley, "Exploiting functional relationships in musical composition," Connection Science Special Issue on Music, Brain, and Cognition, 2009, to appear. J. Lander, "The ocean spray in your face," Game Developer Magazine, pp. 13-20, July 1997.

J. V. der Berg, "Building an advanced particle system," Game Developer Magazine, pp. 44-50, March 2000. http://dx.doi.org/10.1109/NSSMIC.1992.301266

E. Hastings, R. Guha, and K. O. Stanley, "Interactive evolution of particle systems for computer graphics and animation," IEEE Transactions on Evolutionary Computation, 2009. http://dx.doi.org/10.1109/TEVC.2008.2004261

K. Sims, "Evolving virtual creatures," in Proceedings of the ACM Special Interest Group on Graphics and Interactive Techniques, 1994, pp. 50-62. http://dx.doi.org/10.1145/192161.192167

H. Takagi, "Interactive evolutionary computation: Fusion of the capacities of EC optimization and human evaluation," Proceedings of the IEEE, vol. 89, no. 9, pp. 1275-1296, 2001. http://dx.doi.org/10.1109/5.949485

C. Reynolds, "Steering behaviors of autonomous characters," in Proceedings of the Game Developers Conference, 1999, pp. 763-782.

-, "Flocks, herds, and schools: A distributed behavioral model," in Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, 1987, pp. 25 - 34. http://dx.doi.org/10.1145/37401.37406


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