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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Decomposition Strategies for Constructive Preference Elicitation

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Paolo Dragone

University of Trento


Stefano Teso

KU Leuven


Mohit Kumar

KU Leuven


Andrea Passerini

University of Trento


DOI:

10.1609/aaai.v32i1.11800


Abstract:

We tackle the problem of constructive preference elicitation, that is the problem of learning user preferences over verylarge decision problems, involving a combinatorial space of possible outcomes. In this setting, the suggested configuration is synthesized on-the-fly by solving a constrained optimization problem, while the preferences are learned iteratively by interacting with the user. Previous work has shown that Coactive Learning is a suitable method for learning userpreferences in constructive scenarios. In Coactive Learning the user provides feedback to the algorithm in the form of an improvement to a suggested configuration. When the problem involves many decision variables and constraints, this type of interaction poses a significant cognitive burden on the user. We propose a decomposition technique for large preference-based decision problems relying exclusively on inference and feedback over partial configurations. This has the clear advantage of drastically reducing the user cognitive load. Additionally, part-wise inference can be (up to exponentially) less computationally demanding than inference over full configurations. We discuss the theoretical implications of working with parts and present promising empirical results on one synthetic and two realistic constructive problems.

Topics: AAAI

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Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini Decomposition Strategies for Constructive Preference Elicitation Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini Decomposition Strategies for Constructive Preference Elicitation AAAI 2018, .

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini (2018). Decomposition Strategies for Constructive Preference Elicitation. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini. Decomposition Strategies for Constructive Preference Elicitation. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini. 2018. Decomposition Strategies for Constructive Preference Elicitation. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini. (2018) "Decomposition Strategies for Constructive Preference Elicitation", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini, "Decomposition Strategies for Constructive Preference Elicitation", AAAI, p., 2018.

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini. "Decomposition Strategies for Constructive Preference Elicitation". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini. "Decomposition Strategies for Constructive Preference Elicitation". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Paolo Dragone||Stefano Teso||Mohit Kumar||Andrea Passerini. Decomposition Strategies for Constructive Preference Elicitation. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
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