Cookies Policy

This site uses cookies. By continuing to browse the site you are agreeing to our use of cookies.

I accept this policy

Find out more here


No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.

Brill’s MyBook program is exclusively available on BrillOnline Books and Journals. Students and scholars affiliated with an institution that has purchased a Brill E-Book on the BrillOnline platform automatically have access to the MyBook option for the title(s) acquired by the Library. Brill MyBook is a print-on-demand paperback copy which is sold at a favorably uniform low price.

Access this article

+ Tax (if applicable)
Add to Favorites
You must be logged in to use this functionality

image of Behaviour

In complex and stochastic environments the ability to cope with the unexpected is essential for survival. This paper describes a motivational framework founded on the need to reduce uncertainty. It is centred around a merging of classifier systems, taken from the field of artificial intelligence, with the information-primacy approach to animal motivation. It is proposed that in order to deal with uncertainty the animal constructs cognitive models of its environment that are composed of hierarchies of condition-action rules. There is parallel activation of several rules at any given time, and these rules compete to determine behaviour. The rules found to be the best predictors (and may in addition have resulted in reinforcement) gain strength, whilst the less successful rules lose strength over time. Unexpected events trigger the generation of families of new rules which are then subject to environmental selection. The efficient operation of the cognitive model requires the continual reduction of uncertainty, so that information-gathering behaviour forms a substratum upon which other, more obviously goal directed, behaviours occur. High need states can break into this ongoing behaviour and give it a special direction. The framework is related to the inherent variability of behaviour, the failure of certain reinforcement contingencies to control behaviour, and approach/avoidance behaviour towards novel stimuli.

Affiliations: 1: Central Science Laboratory, Ministry of Agriculture, Fisheries & Food, Sand Hutton, York YO41 1LZ


Full text loading...


Data & Media loading...

Article metrics loading...



Can't access your account?
  • Tools

  • Add to Favorites
  • Printable version
  • Email this page
  • Subscribe to ToC alert
  • Get permissions
  • Recommend to your library

    You must fill out fields marked with: *

    Librarian details
    Your details
    Why are you recommending this title?
    Select reason:
    Behaviour — Recommend this title to your library
  • Export citations
  • Key

  • Full access
  • Open Access
  • Partial/No accessInformation