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Recent Developments in Learning and Competition with Finite Automata (Extended Abstract)

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Internet and Network Economics (WINE 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4286))

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Abstract

Consider a repeated two-person game. The question is how much smarter should a player be to effectively predict the moves of the other player. The answer depends on the formal definition of effective prediction, the number of actions each player has in the stage game, as well as on the measure of smartness. Effective prediction means that, no matter what the stage-game payoff function, the player can play (with high probability) a best reply in most stages. Neyman and Spencer [4] provide a complete asymptotic solution when smartness is measured by the size of the automata that implement the strategies.

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References

  1. Ben-Porath, E.: Repeated games with finite automata. Journal of Economic Theory 59, 17–32 (1993)

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  2. Neyman, A.: Cooperation, repetition, and automata. In: Hart, S., Mas Colell, A. (eds.) Cooperation: Game-Theoretic Approaches. NATO ASI Series F, vol. 155, pp. 233–255. Springer, Heidelberg (1997)

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  3. Neyman, A.: The strategic value of memory (tentative title) (forthcoming, 2006)

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  4. Neyman, A., Spencer, J.: The complexity threshold for effective prediction (tentative title) (forthcoming, 2006)

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  5. Neyman, A., Okada, D.: Two-person repeated games with finite automata. International Journal of Game Theory 29, 309–325 (2000)

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Author information

Authors and Affiliations

  1. Institute of Mathematics and Center for the Study of Rationality, The Hebrew University of Jerusalem, Givat Ram, Jerusalem, 91904, Israel

    Abraham Neyman

Authors
  1. Abraham Neyman
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering and Informatics, University of Patras, 26500, Rio, Patras, Greece

    Paul Spirakis

  2. Department of Computer Science, University of Cyprus, CY-1678, Nicosia, Cyprus

    Marios Mavronicolas

  3. R.A. Computer Technology Institute, N. Kazantzakis Str., University Campus, 26500, Rio–Patra, Greece

    Spyros Kontogiannis

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© 2006 Springer-Verlag Berlin Heidelberg

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Neyman, A. (2006). Recent Developments in Learning and Competition with Finite Automata (Extended Abstract). In: Spirakis, P., Mavronicolas, M., Kontogiannis, S. (eds) Internet and Network Economics. WINE 2006. Lecture Notes in Computer Science, vol 4286. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11944874_1

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  • DOI: https://doi.org/10.1007/11944874_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68138-0

  • Online ISBN: 978-3-540-68141-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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