Abstract
Complete tablebases, indicating best moves for every position, exist for chess endgames. There is no doubt that tablebases contain a wealth of knowledge, however, mining for this knowledge, manually or automatically, proved as extremely difficult. Recently, we developed an approach that combines specialized minimax search with the argument-based machine learning (ABML) paradigm. In this paper, we put this approach to test in an attempt to elicit human-understandable knowledge from tablebases. Specifically, we semi-automatically synthesize knowledge from the KBNK tablebase for teaching the difficult king, bishop, and knight versus the lone king endgame.
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References
Thompson, K.: Retrograde analysis of certain endgames. International Computer Chess Association Journal 9(3), 131–139 (1986)
Roycroft, A.J.: Expert against oracle. In: Hayes, J.E., Michie, D., Richards, J. (eds.) Machine Intelligence, vol. 11, pp. 347–373. Oxford University Press, Oxford (1988)
Nunn, J.: Secrets of Minor-Piece Endings. Batsford (1995)
Nunn, J.: Secrets of Pawnless Endings. Gambit Publications Limited (2002)
Fürnkranz, J.: Machine learning in games: A survey. In: Fürnkranz, J., Kubat, M. (eds.) Machines that Learn to Play Games. Nova Scientific Publishers, New York (2001)
van den Herik, H., Uiterwijk, J., van Rijswijck, J.: Games solved: Now and in the future. Artificial Intelligence 134, 277–311 (2002)
Možina, M., Guid, M., Krivec, J., Sadikov, A., Bratko, I.: Fighting knowledge acquisition bottleneck with argument based machine learning. In: The 18th European Conference on Artificial Intelligence (ECAI), pp. 234–238 (2008)
Guid, M., Možina, M., Krivec, J., Sadikov, A., Bratko, I.: Learning positional features for annotating chess games: A case study. In: van den Herik, H.J., Xu, X., Ma, Z., Winands, M.H.M. (eds.) CG 2008. LNCS, vol. 5131, pp. 192–204. Springer, Heidelberg (2008)
Možina, M., Guid, M., Sadikov, A., Bratko, I.: Goal-Based Rule Learning. Technical report, Faculty of Computer and Information Science, University of Ljubljana, Slovenia (2009), http://www.ailab.si/matej/KBNK/GBRL.pdf
Bratko, I.: Knowledge-based problem-solving in AL3. Machine Intelligence 10, 73–100 (1982)
Možina, M., Žabkar, J., Bratko, I.: Argument based machine learning. Artificial Intelligence 171(10/15), 922–937 (2007)
Delétang, D.: Mat avec le fou et le cavalier. Las Stratgie 56(2), 25–32 (1923)
Dvoretsky, M.: Dvoretsky’s Endgame Manual, 2nd edn. Russell Enterprises, Inc. (2008)
van den Herik, H.J.: Representation of experts’ knowledge in a subdomain of chess intelligence. In: IJCAI, pp. 252–255 (1983)
Bramer, M.: Representation of knowledge for chess endgames: towards a self-improving system. PhD thesis, The Open University: Faculty of Mathematics, Milton Keynes, England (1977)
van den Herik, H.J.: Computerschaak, Schaakwereld en Kunstmatige Intelligentie. PhD thesis, Delft University of Technology, Academic Service, The Hague (1983)
van den Herik, H.J., Herschberg, I.: Omniscience, the rulegiver? In: Pernici, B., Somalvico, M. (eds.) Proceedings of L’Intelligenza Artificiale Ed Il Gioco Degli Scacchi, III Convegno Internazionale, pp. 1–17 (1986)
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Guid, M., Možina, M., Sadikov, A., Bratko, I. (2010). Deriving Concepts and Strategies from Chess Tablebases. In: van den Herik, H.J., Spronck, P. (eds) Advances in Computer Games. ACG 2009. Lecture Notes in Computer Science, vol 6048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12993-3_18
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DOI: https://doi.org/10.1007/978-3-642-12993-3_18
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