Literature DB >> 16224728

Info-gap robust-satisficing model of foraging behavior: do foragers optimize or satisfice?

Yohay Carmel1, Yakov Ben-Haim.   

Abstract

In this note we compare two mathematical models of foraging that reflect two competing theories of animal behavior: optimizing and robust satisficing. The optimal-foraging model is based on the marginal value theorem (MVT). The robust-satisficing model developed here is an application of info-gap decision theory. The info-gap robust-satisficing model relates to the same circumstances described by the MVT. We show how these two alternatives translate into specific predictions that at some points are quite disparate. We test these alternative predictions against available data collected in numerous field studies with a large number of species from diverse taxonomic groups. We show that a large majority of studies appear to support the robust-satisficing model and reject the optimal-foraging model.

Mesh:

Year:  2005        PMID: 16224728     DOI: 10.1086/491691

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  4 in total

1.  Natural search algorithms as a bridge between organisms, evolution, and ecology.

Authors:  Andrew M Hein; Francesco Carrara; Douglas R Brumley; Roman Stocker; Simon A Levin
Journal:  Proc Natl Acad Sci U S A       Date:  2016-08-05       Impact factor: 11.205

2.  Correlated decision making across multiple phases of olfactory-guided search in Drosophila improves search efficiency.

Authors:  Floris van Breugel
Journal:  J Exp Biol       Date:  2021-08-20       Impact factor: 3.308

3.  Robust versus optimal strategies for two-alternative forced choice tasks.

Authors:  M Zacksenhouse; R Bogacz; P Holmes
Journal:  J Math Psychol       Date:  2010-01-13       Impact factor: 2.223

4.  Info-gap management of public health Policy for TB with HIV-prevalence and epidemiological uncertainty.

Authors:  Yakov Ben-Haim; Clifford C Dacso; Nicola M Zetola
Journal:  BMC Public Health       Date:  2012-12-19       Impact factor: 3.295

  4 in total

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