Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

A three-neuron model of information processing during Bayesian foraging

In English

Författare

Summary, in English

A foraging animal is often confronted with uncertainty of resource abundance. A Bayesian model provides the optimal forgaing policy when food occurrence is patchy. The solution of the Bayesian foraging policy requires elaborate calculations and it is unclear to what extent the policy could be implemented in a neural system. Here we suggest a network architecture of three neurones that approximately can perform an optimal Bayesian foraging policy. It remains to be shown how the network could be self-learned e.g. through Hebbian learning, and how close to to the optimal policy it can perform.

Publiceringsår

2000

Språk

Engelska

Sidor

265-270

Publikation/Tidskrift/Serie

Artificial Neural Networks In Medicine and Biology (Perspectives In Neural Computing)

Dokumenttyp

Konferensbidrag

Förlag

Springer

Ämne

  • Ecology

Status

Published

Forskningsgrupp

  • Biodiversity and Conservation Science

ISBN/ISSN/Övrigt

  • ISSN: 1431-6854
  • ISBN: 1-85233-289-1