Bayesian mechanics for stationary processes

Da Costa, Lancelot; Friston, Karl; Heins, Conor; Pavliotis, Grigorios A.

Bayesian mechanics for stationary processes

Dateien

DaCosta_2-71cm7stsluyo6.pdfGröße: 2.05 MBDownloads: 143

Datum

2021

Autor:innen

Da Costa, Lancelot

Friston, Karl

Heins, Conor

Pavliotis, Grigorios A.

Open Access-Veröffentlichung

Open Access Hybrid

Sammlungen

Biologie
Exzellenzcluster "Centre for the Advanced Study of Collective Behaviour"

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Proceedings of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences. Royal Society of London. 2021, 477(2256), 20210518. ISSN 1364-5021. eISSN 1471-2946. Available under: doi: 10.1098/rspa.2021.0518

Zusammenfassung

This paper develops a Bayesian mechanics for adaptive systems. Firstly, we model the interface between a system and its environment with a Markov blanket. This affords conditions under which states internal to the blanket encode information about external states. Second, we introduce dynamics and represent adaptive systems as Markov blankets at steady state. This allows us to identify a wide class of systems whose internal states appear to infer external states, consistent with variational inference in Bayesian statistics and theoretical neuroscience. Finally, we partition the blanket into sensory and active states. It follows that active states can be seen as performing active inference and well-known forms of stochastic control (such as PID control), which are prominent formulations of adaptive behaviour in theoretical biology and engineering.

Fachgebiet (DDC)

570 Biowissenschaften, Biologie

Zitieren

ISO 690

DA COSTA, Lancelot, Karl FRISTON, Conor HEINS, Grigorios A. PAVLIOTIS, 2021. Bayesian mechanics for stationary processes. In: Proceedings of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences. Royal Society of London. 2021, 477(2256), 20210518. ISSN 1364-5021. eISSN 1471-2946. Available under: doi: 10.1098/rspa.2021.0518

BibTex

@article{DaCosta2021Bayes-55927,
  year={2021},
  doi={10.1098/rspa.2021.0518},
  title={Bayesian mechanics for stationary processes},
  number={2256},
  volume={477},
  issn={1364-5021},
  journal={Proceedings of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences},
  author={Da Costa, Lancelot and Friston, Karl and Heins, Conor and Pavliotis, Grigorios A.},
  note={Article Number: 20210518}
}

RDF

<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/55927">
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Pavliotis, Grigorios A.</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:creator>Heins, Conor</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43615"/>
    <dcterms:issued>2021</dcterms:issued>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/55927"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/55927/1/DaCosta_2-71cm7stsluyo6.pdf"/>
    <dc:contributor>Da Costa, Lancelot</dc:contributor>
    <dcterms:title>Bayesian mechanics for stationary processes</dcterms:title>
    <dc:contributor>Friston, Karl</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43615"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-12-20T08:41:06Z</dcterms:available>
    <dc:contributor>Heins, Conor</dc:contributor>
    <dc:language>eng</dc:language>
    <dcterms:abstract xml:lang="eng">This paper develops a Bayesian mechanics for adaptive systems. Firstly, we model the interface between a system and its environment with a Markov blanket. This affords conditions under which states internal to the blanket encode information about external states. Second, we introduce dynamics and represent adaptive systems as Markov blankets at steady state. This allows us to identify a wide class of systems whose internal states appear to infer external states, consistent with variational inference in Bayesian statistics and theoretical neuroscience. Finally, we partition the blanket into sensory and active states. It follows that active states can be seen as performing active inference and well-known forms of stochastic control (such as PID control), which are prominent formulations of adaptive behaviour in theoretical biology and engineering.</dcterms:abstract>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/55927/1/DaCosta_2-71cm7stsluyo6.pdf"/>
    <dc:contributor>Pavliotis, Grigorios A.</dc:contributor>
    <dc:creator>Da Costa, Lancelot</dc:creator>
    <dc:creator>Friston, Karl</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-12-20T08:41:06Z</dc:date>
  </rdf:Description>
</rdf:RDF>

Begutachtet

Ja