Kolkata Paise Restaurant Problem in Some Uniform Learning Strategy Limits

  • Asim Ghosh
  • Anindya Sundar Chakrabarti
  • Bikas K. Chakrabarti
Part of the New Economic Windows book series (NEW)


We study the dynamics of some uniform learning strategy limits or a probabilistic version of the “Kolkata Paise Restaurant” problem, where N agents choose among N equally priced but differently ranked restaurants every evening such that each agent can get dinner in the best possible ranked restaurant (each serving only one customer and the rest arriving there going without dinner that evening). We consider the learning to be uniform among the agents and assume that each follow the same probabilistic strategy dependent on the information of the past successes in the game. The numerical results for utilization of the restaurants in some limiting cases are analytically examined.


Numerical Simulation Result Average Fraction Strategy Limit Indian Statistical Institute Probabilistic Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    A.S. Chakrabarti, B.K. Chakrabarti, A. Chatterjee, M. Mitra, The Kolkata Paise Restaurant Problem and Resource Utilization, Physica A 388 (2009) 2420–2426CrossRefGoogle Scholar
  2. 2.
    B.K. Chakrabarti, Kolkata Restaurant Problem as a generalised El Farol Bar Problem, in Econophysics of Markets and Business Networks, Eds. A. Chatterjee and B. K. Chakrabarti, New Economic Windows Series Springer, Milan (2007), pp. 239–246CrossRefGoogle Scholar
  3. 3.
    D. Challet, M. Marsili, Y.-C. Zhang, Minority Games: Interacting Agents in Financial Markets, Oxford University Press, Oxford (2005)Google Scholar
  4. 4.
    D. Challet, Model of Financial Market Information Ecology, in Econophysics of Stock and Orther Markets, Eds. A. Chatterjee and B. K. Chakrabarti, Springer, Milan (2006) pp. 101–112CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Italia 2010

Authors and Affiliations

  • Asim Ghosh
    • 1
  • Anindya Sundar Chakrabarti
    • 2
  • Bikas K. Chakrabarti
    • 3
    • 4
  1. 1.Theoretical Condensed Matter Physics DivisionSaha Institute of Nuclear PhysicsKolkataIndia
  2. 2.Indian Statistical InstituteKolkataIndia
  3. 3.Centre for Applied Mathematics & Computational Science and Theoretical Condensed Matter Physics DivisionSaha Institute of Nuclear PhysicsKolkataIndia
  4. 4.Economic Research UnitIndian Statistical InstituteKolkataIndia

Personalised recommendations