Abstract
Game AI is a well-established area of research. Classic strategy board games such as Chess and Go have been the subject of AI research for several decades, and more recently modern computer games have come to be seen as a valuable test-bed for AI methods and technologies. Modern board games, in particular those known as German-Style Board Games or Eurogames, are an interesting mid-point between these fields in terms of domain complexity, but AI research in this area is more sparse. This paper discusses the design, development and performance of a game-playing agent, called SCOUT, that uses the Case-Based Reasoning methodology as a means to reason and make decisions about game states in the Eurogame Race for the Galaxy. The purpose of this research is to explore the possibilities and limitations of Case-Based Reasoning within the domain of Race for the Galaxy and Eurogames in general.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aha, D.W., Molineaux, M., Ponsen, M.: Learning to win: case-based plan selection in a real-time strategy game. In: Muñoz-Ávila, H., Ricci, F. (eds.) ICCBR 2005. LNCS, vol. 3620, pp. 5–20. Springer, Heidelberg (2005). doi:10.1007/11536406_4
Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Commun. 7(1), 39–59 (1994)
Auslander, B., Lee-Urban, S., Hogg, C., Muñoz-Avila, H.: Recognizing the enemy: combining reinforcement learning with strategy selection using case-based reasoning. In: Althoff, K.-D., Bergmann, R., Minor, M., Hanft, A. (eds.) ECCBR 2008. LNCS, vol. 5239, pp. 59–73. Springer, Heidelberg (2008). doi:10.1007/978-3-540-85502-6_4
Campbell, M., Hoane, A.J., Hsu, F.: Deep blue. Artif. Intell. 134(1), 57–83 (2002)
Fogel, D.: Blondie24: Playing at the Edge of AI. Morgan Kaufmann, Burlington (2001)
Heyden, C.: Implementing a computer player for Carcassonne. Master’s thesis, Maastricht University (2009)
Jones, K.: Race for the Galaxy AI. www.keldon.net/rftg. Accessed 22 Oct 2016
Laird, J., VanLent, M.: Human-level AI’s killer application: interactive computer games. AI Mag. 22(2), 15 (2001)
Lehmann, T.: Game Preview: Race for the Galaxy, 26 September 2008. Boardgame News
Molineaux, M., Aha, D.W.: TIELT: a testbed for gaming environments. In: AAAI 2005, p. 1690. AAAI Press (2005)
Powell, J., Hauff, B., Hastings, J.: Utilizing case-based reasoning and automatic case elicitation to develop a self-taught knowledgeable agent. In: Challenges in Game Artificial Intelligence: Papers from the AAAI Workshop (2004)
Reyes, O., Morell, C., Ventura, S.: Evolutionary feature weighting to improve the performance of multi-label lazy algorithms. Integr. Comput.-Aided Eng. 21(4), 339–354 (2014)
Richter, M.M., Weber, R.O.: Case-Based Reasoning. Springer, Heidelberg (2013)
Rio Grande Games. Race for the Galaxy. http://riograndegames.com/Game/240-Race-for-the-Galaxy. Accessed 22 Oct 2016
Rubin, J., Watson, I.: Investigating the effectiveness of applying case-based reasoning to the game of Texas Hold’em. In: FLAIRS Conference, pp. 417–422 (2007)
Schaeffer, J., Burch, N., Bjornsson, Y., Kishimoto, A., Muller, M., Lake, R., Lu, P., Sutphen, S.: Checkers is solved. Science 317(5844), 1518–1522 (2007)
Silver, D., Huang, A., Maddison, C., Guez, A., Sifre, L., Van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M.: Mastering the game of Go with deep neural networks and tree search. Nature 529(7587), 484–489 (2016)
Sinclair, D.: Using example-based reasoning for selective move generation in two player adversarial games. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS, vol. 1488, pp. 126–135. Springer, Heidelberg (1998). doi:10.1007/BFb0056327
Szita, I., Chaslot, G., Spronck, P.: Monte-carlo tree search in settlers of catan. In: Herik, H.J., Spronck, P. (eds.) ACG 2009. LNCS, vol. 6048, pp. 21–32. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12993-3_3
Wender, S., Watson, I.: Combining case-based reasoning and reinforcement learning for unit navigation in real-time strategy game AI. In: Lamontagne, L., Plaza, E. (eds.) ICCBR 2014. LNCS, vol. 8765, pp. 511–525. Springer, Cham (2014). doi:10.1007/978-3-319-11209-1_36
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Woolford, M., Watson, I. (2017). SCOUT: A Case-Based Reasoning Agent for Playing Race for the Galaxy. In: Aha, D., Lieber, J. (eds) Case-Based Reasoning Research and Development. ICCBR 2017. Lecture Notes in Computer Science(), vol 10339. Springer, Cham. https://doi.org/10.1007/978-3-319-61030-6_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-61030-6_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-61029-0
Online ISBN: 978-3-319-61030-6
eBook Packages: Computer ScienceComputer Science (R0)