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Predictive regulation in affective and adaptive behaviour: An allostatic-cybernetics perspective
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. University of Gothenburg, Sweden . (Interaction Lab (ILAB))ORCID iD: 0000-0002-1525-0745
University of Gothenburg, Sweden.
University of Gothenburg, Sweden.
2017 (English)In: Advanced Research on Biologically Inspired Cognitive Architectures / [ed] Jordi Vallverdú, Manuel Mazzara, Max Talanov, Salvatore Distefano and Robert Lowe, IGI Global, 2017, p. 149-176Chapter in book (Other academic)
Abstract [en]

In this chapter, different notions of allostasis (the process of achieving stability through change ) as they apply to adaptive behavior are presented. The authors discuss how notions of allostasis can be usefully applied to Cybernetics-based homeostatic systems. Particular emphasis is placed upon affective states - motivational and emotional - and, above all, the notion of 'predictive' regulation, as distinct from forms of 'reactive' regulation, in homeostatic systems. The authors focus here on Ashby's ultrastability concept that entails behavior change for correcting homeostatic errors (deviations from the healthy range of essential, physiological, variables). The authors consider how the ultrastability concept can be broadened to incorporate allostatic mechanisms and how they may enhance adaptive physiological and behavioral activity. Finally, this chapter references different Cybernetics frameworks that incorporate the notion of allostasis. The article then attempts to untangle how the given perspectives fit into the 'allostatic ultrastable systems' framework postulated. 

Place, publisher, year, edition, pages
IGI Global, 2017. p. 149-176
Series
Advances in Computational Intelligence and Robotics (ACIR), ISSN 2327-0411, E-ISSN 2327-042X
National Category
Computer and Information Sciences
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-14569DOI: 10.4018/978-1-5225-1947-8.ch008ISI: 000411555200009Scopus ID: 2-s2.0-85027510045ISBN: 978-1-5225-1948-5 (electronic)ISBN: 978-1-5225-1947-8 (print)ISBN: 1-5225-1947-5 (print)OAI: oai:DiVA.org:his-14569DiVA, id: diva2:1163723
Available from: 2017-12-07 Created: 2017-12-07 Last updated: 2024-05-21Bibliographically approved

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