Abstract
In games with imperfect information, the ‘information set’ is a collection of all possible game histories that are consistent with, or explain, a player’s observations. Current game playing systems rely on these best guesses of the true, partially-observable game as the foundation of their decision making, yet finding these information sets is expensive.
We apply reactive Answer Set Programming (ASP) to the problem of sampling information sets in the field of General Game Playing. Furthermore, we use this domain as a test bed for evaluating the effectiveness of oClingo, a reactive answer set solver, in avoiding redundant search by keeping learnt clauses during incremental solving.
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
Preview
Unable to display preview. Download preview PDF.
References
Baral, C.: Knowledge Representation, Reasoning, and Declarative Problem Solving. Cambridge University Press, New York (2003)
Edelkamp, S., Federholzner, T., Kissmann, P.: Searching with partial belief states in general games with incomplete information. In: Glimm, B., Krüger, A. (eds.) KI 2012. LNCS, vol. 7526, pp. 25–36. Springer, Heidelberg (2012)
Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T., Thiele, S.: Engineering an incremental ASP solver. In: Garcia de la Banda, M., Pontelli, E. (eds.) ICLP 2008. LNCS, vol. 5366, pp. 190–205. Springer, Heidelberg (2008)
Genesereth, M.R., Love, N., Pell, B.: General game playing: Overview of the AAAI competition. AI Magazine 26(2), 62–72 (2005), http://games.stanford.edu/competition/misc/aaai.pdf
Long, J.R., Sturtevant, N.R., Buro, M., Furtak, T.: Understanding the success of perfect information monte carlo sampling in game tree search. In: Fox, M., Poole, D. (eds.) AAAI. AAAI Press (2010)
Love, N., Hinrichs, T., Haley, D., Schkufza, E., Genesereth, M.: General game playing: Game description language specification. Tech. Rep. LG–2006–01, Stanford Logic Group (2006)
Rasmusen, E.: Games and Information: an Introduction to Game Theory, 4th edn. Blackwell Publishing (2007)
Richards, M., Amir, E.: Information set sampling for general imperfect information positional games. In: Proc. IJCAI 2009 Workshop on GGP, GIGA 2009, pp. 59–66 (2009)
Saffidine, A., Cazenave, T.: A forward chaining based game description language compiler. In: Proc. IJCAI 2011 Workshop on GGP, GIGA 2011 (July 2011)
Schofield, M., Cerexhe, T., Thielscher, M.: Hyperplay: A solution to general game playing with imperfect information. In: Proc. AAAI, Toronto (July 2012)
Simons, P., Niemelá, I., Soininen, T.: Extending and implementing the stable model semantics. Artificial Intelligence 138(1-2), 181–234 (2002)
Thielscher, M.: Answer set programming for single-player games in general game playing. In: Hill, P.M., Warren, D.S. (eds.) ICLP 2009. LNCS, vol. 5649, pp. 327–341. Springer, Heidelberg (2009)
Thielscher, M.: A general game description language for incomplete information games. In: Proc. AAAI, Atlanta, pp. 994–999 (July 2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cerexhe, T., Sabuncu, O., Thielscher, M. (2013). Evaluating Answer Set Clause Learning for General Game Playing. In: Cabalar, P., Son, T.C. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2013. Lecture Notes in Computer Science(), vol 8148. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40564-8_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-40564-8_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40563-1
Online ISBN: 978-3-642-40564-8
eBook Packages: Computer ScienceComputer Science (R0)