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algorithm to construct them from the game rules and demonstrated the transformation
from fluent graph distance to a distance feature.
Unlike previous distance estimations, our approach does not rely on syntactic pat-
terns or internal simulations. Moreover, it preserves piece-dependent move patterns and
produces an admissible distance heuristic.
We showed on an example how these distance features can be used in a state evalu-
ation function. We gave two examples on how distance estimates can improve the state
evaluation and evaluated our distance against Fluxplayer in its most recent version.
Certain shortcomings should be addressed to improve the efficiency of fluent graph
construction and the quality of the obtained distance function. Despite these shortcom-
ings, we found that a state evaluation function using the new distance estimates can
compete with a state-of-the-art system.
References
1. Bonet, B., Geffner, H.: Planning as heuristic search. Artificial Intelligence 129(1-2), 5-33
(2001)
2. Clune, J.: Heuristic evaluation functions for general game playing. In: Proceedings of the
AAAI Conference on Artificial Intelligence, pp. 1134-1139. AAAI Press (2007)
3. Hoffmann, J., Nebel, B.: The FF planning system: Fast plan generation through heuristic
search. JAIR 14, 253-302 (2001)
4. Kaiser, D.M.: Automatic feature extraction for autonomous general game playing agents. In:
Proceedings of the Sixth Intl. Joint Conf. on Autonomous Agents and Multiagent Systems
(2007)
5. Kissmann, P., Edelkamp, S.: Instantiating General Games Using Prolog or Dependency
Graphs. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds.) KI 2010. LNCS,
vol. 6359, pp. 255-262. Springer, Heidelberg (2010)
6. Kuhlmann, G., Dresner, K., Stone, P.: Automatic Heuristic Construction in a Complete Gen-
eral Game Player. In: Proceedings of the Twenty-First National Conference on Artificial
Intelligence, pp. 1457-1462. AAAI Press, Boston (2006)
7. Love, N., Hinrichs, T., Haley, D., Schkufza, E., Genesereth, M.: General game playing: Game
description language specification. Tech. Rep., Stanford University (March 4, 2008), the most
recent version should be available at http://games.stanford.edu/
8. Pell, B.: Strategy generation and evaluation for meta-game playing. Ph.D. thesis, University
of Cambridge (1993)
9. Schiffel, S., Thielscher, M.: Fluxplayer: A successful general game player. In: Proceedings of
the National Conference on Artificial Intelligence, pp. 1191-1196. AAAI Press, Vancouver
(2007)
10. Schiffel, S., Thielscher, M.: Automated theorem proving for general game playing. In: Pro-
ceedings of the International Joint Conference on Artificial Intelligence (IJCAI) (2009)
11. Schiffel, S., Thielscher, M.: A Multiagent Semantics for the Game Description Language.
In: Filipe, J., Fred, A., Sharp, B. (eds.) ICAART 2009. CCIS, vol. 67, pp. 44-55. Springer,
Heidelberg (2010)
 
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