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dc.contributor.authorRiegler, Bente
dc.contributor.authorPolani, Daniel
dc.contributor.editorFellermann, Harold
dc.contributor.editorBacardit, Jaume
dc.contributor.editorGoñi-Moreno, Ángel
dc.contributor.editorFüchslin, Rudolf
dc.date.accessioned2019-12-19T01:01:24Z
dc.date.available2019-12-19T01:01:24Z
dc.date.issued2019-07
dc.identifier.citationRiegler , B & Polani , D 2019 , On information-optimal scripting of actions . in H Fellermann , J Bacardit , Á Goñi-Moreno & R Füchslin (eds) , Alife 2019 : Proceedings of the Artificial Life Conference 2019 . MIT Press , pp. 624-625 , The 2019 Conference on Artificial Life , Newcastle , United Kingdom , 29/07/19 . https://doi.org/10.1162/isal_a_00230
dc.identifier.citationconference
dc.identifier.otherPURE: 16789194
dc.identifier.otherPURE UUID: 14531f0f-4169-48c0-aaf8-cd4f73dd4c55
dc.identifier.otherORCID: /0000-0002-3233-5847/work/86098056
dc.identifier.urihttp://hdl.handle.net/2299/22016
dc.descriptionBest paper award.
dc.description.abstractAnimals and humans encounter many tasks which permit ritualized behaviours, essentially fixed action sequences or “scripts”, similar to options known from Reinforcement Learning, but proceeding without intermediate decisions. While running a script, they proceed in an open-loop fashion. However even when these are already known, an agent needs to decide whether to perform a basic action or to trigger a script regarding the particular task. Here we study if including such scripts (i.e. behaviour rituals) is advantageous from the point of view of the relevant information required to take the decision to start such a script depending on the tasks. To achieve this, we modify the relevant information framework including sequences of basic actions to the possible actions.en
dc.format.extent2
dc.language.isoeng
dc.publisherMIT Press
dc.relation.ispartofAlife 2019
dc.titleOn information-optimal scripting of actionsen
dc.contributor.institutionAdaptive Systems
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionSchool of Computer Science
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1162/isal_a_00230
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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