Restricting the Maximum Number of Actions for Decision Support Under Uncertainty

GEHRKE, Marcel, BRAUN, Tanya and POLOVINA, Simon (2020). Restricting the Maximum Number of Actions for Decision Support Under Uncertainty. In: ALAM, Mehwish, BRAUN, Tanya and YUN, Bruno, (eds.) Ontologies and Concepts in Mind and Machine. Lecture Notes in Computer Science (12277). Springer Nature Switzerland AG 2020, 145-160.

[img]
Preview
PDF
iccs20.pdf - Accepted Version
All rights reserved.

Download (391kB) | Preview
Official URL: https://link.springer.com/chapter/10.1007/978-3-03...
Link to published version:: https://doi.org/10.1007/978-3-030-57855-8_11
Related URLs:

    Abstract

    Standard approaches for decision support are computing a maximum expected utility or solving a partially observable Markov decision process. To the best of our knowledge, in both approaches, external restrictions are not accounted for. However, restrictions to actions often exists, for example in the form of limited resources. We demonstrate that restrictions to actions can lead to a combinatorial explosion if performed on a ground level, making ground inference intractable. Therefore, we extend a formalism that solves a lifted maximum expected utility problem to handle restricted actions. To test its relevance, we apply the new formalism to enterprise architecture analysis.

    Item Type: Book Section
    Additional Information: 25th International Conference on Conceptual Structures, ICCS 2020, Bolzano, Italy, September 18–20, 2020, Proceedings Series Online ISSN 1611-3349
    Identification Number: https://doi.org/10.1007/978-3-030-57855-8_11
    Page Range: 145-160
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 07 Oct 2020 14:41
    Last Modified: 10 Sep 2021 01:18
    URI: https://shura.shu.ac.uk/id/eprint/27362

    Actions (login required)

    View Item View Item

    Downloads

    Downloads per month over past year

    View more statistics