Literature DB >> 22085791

Is optimism optimal? Functional causes of apparent behavioural biases.

Alasdair I Houston1, Pete C Trimmer, Tim W Fawcett, Andrew D Higginson, James A R Marshall, John M McNamara.   

Abstract

We review the use of the terms 'optimism' and 'pessimism' to characterize particular types of behaviour in non-human animals. Animals can certainly behave as though they are optimistic or pessimistic with respect to specific motivations, as documented by an extensive range of examples in the literature. However, in surveying such examples we find that these terms are often poorly defined and are liable to lead to confusion. Furthermore, when considering behaviour within the framework of optimal decision theory using appropriate currencies, it is often misleading to describe animals as optimistic or pessimistic. There are two common misunderstandings. First, some apparent cases of biased behaviour result from misidentifying the currencies and pay-offs the animals should be maximising. Second, actions that do not maximise short-term pay-offs have sometimes been described as optimistic or pessimistic when in fact they are optimal in the long term; we show how such situations can be understood from the perspective of bandit models. Rather than describing suboptimal, unrealistic behaviour, the terms optimism and pessimism are better restricted to informal usage. Our review highlights the importance of choosing the relevant currency when attempting to predict the action of natural selection.
Copyright © 2011 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 22085791     DOI: 10.1016/j.beproc.2011.10.015

Source DB:  PubMed          Journal:  Behav Processes        ISSN: 0376-6357            Impact factor:   1.777


  5 in total

1.  It is optimal to be optimistic about survival.

Authors:  John M McNamara; Pete C Trimmer; Alasdair I Houston
Journal:  Biol Lett       Date:  2012-02-22       Impact factor: 3.703

2.  Sampling and tracking a changing environment: persistence and reward in the foraging decisions of bumblebees.

Authors:  Aimee S Dunlap; Daniel R Papaj; Anna Dornhaus
Journal:  Interface Focus       Date:  2017-04-21       Impact factor: 3.906

3.  Learning, exploitation and bias in games.

Authors:  John M McNamara; Alasdair I Houston; Olof Leimar
Journal:  PLoS One       Date:  2021-02-05       Impact factor: 3.240

4.  Experimental evolution of a more restrained clutch size when filial cannibalism is prevented in burying beetles Nicrophorus vespilloides.

Authors:  Darren Rebar; Chay Halliwell; Rachel Kemp; Rebecca M Kilner
Journal:  Ecol Evol       Date:  2022-04-15       Impact factor: 3.167

5.  Adaptive learning can result in a failure to profit from good conditions: implications for understanding depression.

Authors:  Pete C Trimmer; Andrew D Higginson; Tim W Fawcett; John M McNamara; Alasdair I Houston
Journal:  Evol Med Public Health       Date:  2015-04-26
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.