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.

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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:
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

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