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A Note on Convergence of Adaptive Satisficing to Optimal Stopping

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  • John Conlisk

Abstract

The model concerns a searcher making multiple searches from the same distribution of payoffs. The searcher does not know the distribution, does not attempt to infer it from cumulating information, and does not attempt to compute an optimal stopping rule. Instead the searcher follows thoroughly elementary adaptive rules. Nonetheless, the searcher converges to optimal stopping.

Suggested Citation

  • John Conlisk, 2003. "A Note on Convergence of Adaptive Satisficing to Optimal Stopping," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1353-1360, December.
    • Handle: RePEc:ucp:jpolec:v:111:y:2003:i:6:p:1353-1360
    DOI: 10.1086/378527
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    1. Richard H. Day & E. Herbert Tinney, 1968. "How to Co-operate in Business without Really Trying: A Learning Model of Decentralized Decision Making," Journal of Political Economy, University of Chicago Press, vol. 76, pages 583-583.
    2. Rothschild, Michael, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 689-711, July/Aug..
    3. Kiefer, Nicholas M & Neumann, George R, 1979. "An Empirical Job-Search Model, with a Test of the Constant Reservation-Wage Hypothesis," Journal of Political Economy, University of Chicago Press, vol. 87(1), pages 89-107, February.
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    Cited by:

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    2. Frör, Oliver, 2008. "Bounded rationality in contingent valuation: Empirical evidence using cognitive psychology," Ecological Economics, Elsevier, vol. 68(1-2), pages 570-581, December.

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