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Emergence of distributed coordination in the Kolkata Paise Restaurant problem with finite information

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  • Ghosh, Diptesh
  • Chakrabarti, Anindya S.

Abstract

In this paper, we study a large-scale distributed coordination problem and propose efficient adaptive strategies to solve the problem. The basic problem is to allocate finite number of resources to individual agents in the absence of a central planner such that there is as little congestion as possible and the fraction of unutilized resources is reduced as far as possible. In the absence of a central planner and global information, agents can employ adaptive strategies that uses only a finite knowledge about the competitors. In this paper, we show that a combination of finite information sets and reinforcement learning can increase the utilization fraction of resources substantially.

Suggested Citation

  • Ghosh, Diptesh & Chakrabarti, Anindya S., 2017. "Emergence of distributed coordination in the Kolkata Paise Restaurant problem with finite information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 16-24.
    • Handle: RePEc:eee:phsmap:v:483:y:2017:i:c:p:16-24
    DOI: 10.1016/j.physa.2017.04.171
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    References listed on IDEAS

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    1. Anirban Chakraborti & Damien Challet & Arnab Chatterjee & Matteo Marsili & Yi-Cheng Zhang & Bikas K. Chakrabarti, 2013. "Statistical Mechanics of Competitive Resource Allocation using Agent-based Models," Papers 1305.2121, arXiv.org, revised Sep 2014.
    2. Emanuele Pugliese & Claudio Castellano & Matteo Marsili & Luciano Pietronero, 2009. "Collaborate, compete and share," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 67(3), pages 319-327, February.
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    5. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2013. "Minority Games: Interacting agents in financial markets," OUP Catalogue, Oxford University Press, number 9780199686698.
    6. W. Brian Arthur, 1994. "Inductive Reasoning, Bounded Rationality and the Bar Problem," Working Papers 94-03-014, Santa Fe Institute.
    7. Anirban Chakraborti & Damien Challet & Arnab Chatterjee & Matteo Marsili & Yi-Cheng Zhang & Bikas K. Chakrabarti, 2013. "Statistical Mechanics of Competitive Resource Allocation using Agent-based Models," Papers 1305.2121, arXiv.org, revised Sep 2014.
    8. Chakrabarti, Anindya Sundar & Chakrabarti, Bikas K. & Chatterjee, Arnab & Mitra, Manipushpak, 2009. "The Kolkata Paise Restaurant problem and resource utilization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2420-2426.
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    Cited by:

    1. Anindya S. Chakrabarti & Diptesh Ghosh, 2019. "Emergence of anti-coordination through reinforcement learning in generalized minority games," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 225-245, June.
    2. Kiran Sharma & Anamika & Anindya S. Chakrabarti & Anirban Chakraborti & Sujoy Chakravarty, 2017. "The Saga of KPR: Theoretical and Experimental developments," Papers 1712.06358, arXiv.org.
    3. Kejriwal, Saransh & Sheth, Sarjan & Silpa, P.S. & Sarkar, Sumit & Guha, Apratim, 2022. "Attaining herd immunity to a new infectious disease through multi-stage policies incentivising voluntary vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    4. Kalliopi Kastampolidou & Christos Papalitsas & Theodore Andronikos, 2022. "The Distributed Kolkata Paise Restaurant Game," Games, MDPI, vol. 13(3), pages 1-21, April.
    5. Kalliopi Kastampolidou & Christos Papalitsas & Theodore Andronikos, 2021. "DKPRG or how to succeed in the Kolkata Paise Restaurant gamevia TSP," Papers 2101.07760, arXiv.org.

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