Sequential extensions of causal and evidential decision theory

Tom Everitt*, Jan Leike, Marcus Hutter

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Citations (Scopus)

    Abstract

    Moving beyond the dualistic view in AI where agent and environment are separated incurs new challenges for decision making, as calculation of expected utility is no longer straightforward. The nondualistic decision theory literature is split between causal decision theory and evidential decision theory. We extend these decision algorithms to the sequential setting where the agent alternates between taking actions and observing their consequences.

    Original languageEnglish
    Title of host publicationAlgorithmic Decision Theory - 4th International Conference, ADT 2015, Proceedings
    EditorsToby Walsh
    PublisherSpringer Verlag
    Pages205-221
    Number of pages17
    ISBN (Print)9783319231136
    DOIs
    Publication statusPublished - 2015
    Event4th International Conference on Algorithmic Decision Theory, ADT 2015 - Lexington, United States
    Duration: 27 Sept 201530 Sept 2015

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9346
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference4th International Conference on Algorithmic Decision Theory, ADT 2015
    Country/TerritoryUnited States
    CityLexington
    Period27/09/1530/09/15

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