---
abstract: "We evaluate the ability of artificial neural network models (multi-layer perceptrons) to predict stimulus-­response relationships. A variety of empirical results are considered, such as generalization, peak-shift (supernormality) and stimulus intensity effects. The networks were trained on the same tasks as the animals in the considered experiments. The subsequent generalization tests on the networks showed that the model replicates correctly the empirical results. It is concluded that these models are valuable tools in the study of animal behaviour.\n"
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chapter: ~
commentary: ~
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conference: ~
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contact_email: ~
creators_id: []
creators_name:
  - family: Ghirlanda
    given: Stefano
    honourific: ''
    lineage: ''
  - family: Enquist
    given: Magnus
    honourific: ''
    lineage: ''
date: 1998
date_type: published
datestamp: 2006-12-03
department: ~
dir: disk0/00/00/52/71
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editors_id: []
editors_name: []
eprint_status: archive
eprintid: 5271
fileinfo: /style/images/fileicons/application_pdf.png;/5271/1/ghirlanda_enquist1998.pdf
full_text_status: public
importid: ~
institution: ~
isbn: ~
ispublished: pub
issn: ~
item_issues_comment: []
item_issues_count: 0
item_issues_description: []
item_issues_id: []
item_issues_reported_by: []
item_issues_resolved_by: []
item_issues_status: []
item_issues_timestamp: []
item_issues_type: []
keywords: 'neural networks, animal behavior, generalization'
lastmod: 2011-03-11 08:56:43
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: ~
pagerange: 1383-1389
pubdom: FALSE
publication: Animal Behaviour
publisher: ~
refereed: TRUE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 17:08:34
subjects:
  - bio-etho
  - comp-neuro-sci
  - comp-sci-neural-nets
  - bio-ani-behav
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: Artificial neural networks as models of stimulus control
type: journalp
userid: 6801
volume: 56
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