A three-neuron model of information processing during Bayesian foraging
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