Reasoning and querying bounds on differences with layered preferences. Issue 5 (13th February 2021)
- Record Type:
- Journal Article
- Title:
- Reasoning and querying bounds on differences with layered preferences. Issue 5 (13th February 2021)
- Main Title:
- Reasoning and querying bounds on differences with layered preferences
- Authors:
- Anselma, Luca
Mazzei, Alessandro
Piovesan, Luca
Terenziani, Paolo - Abstract:
- Abstract: Artificial intelligence largely relies on bounds on differences (BoDs) to model binary constraints regarding different dimensions, such as time, space, costs, and calories. Recently, some approaches have extended the BoDs framework in a fuzzy, "noncrisp" direction, considering probabilities or preferences. While previous approaches have mainly aimed at providing an optimal solution to the set of constraints, we propose an innovative class of approaches in which constraint propagation algorithms aim at identifying the "space of solutions" (i.e., the minimal network ) with their preferences, and query answering mechanisms are provided to explore the space of solutions as required, for example, in decision support tasks. Aiming at generality, we propose a class of approaches parametrized over user‐defined scales of qualitative preferences (e.g., Low, Medium, High, and Very High), utilizing the resume and extension operations to combine preferences, and considering different formalisms to associate preferences with BoDs. We consider both "general" preferences and a form of layered preferences that we call "pyramid" preferences. The properties of the class of approaches are also analyzed. In particular, we show that, when the resume and extension operations are defined such that they constitute a closed semiring, a more efficient constraint propagation algorithm can be used. Finally, we provide a preliminary implementation of the constraint propagation algorithms.Abstract: Artificial intelligence largely relies on bounds on differences (BoDs) to model binary constraints regarding different dimensions, such as time, space, costs, and calories. Recently, some approaches have extended the BoDs framework in a fuzzy, "noncrisp" direction, considering probabilities or preferences. While previous approaches have mainly aimed at providing an optimal solution to the set of constraints, we propose an innovative class of approaches in which constraint propagation algorithms aim at identifying the "space of solutions" (i.e., the minimal network ) with their preferences, and query answering mechanisms are provided to explore the space of solutions as required, for example, in decision support tasks. Aiming at generality, we propose a class of approaches parametrized over user‐defined scales of qualitative preferences (e.g., Low, Medium, High, and Very High), utilizing the resume and extension operations to combine preferences, and considering different formalisms to associate preferences with BoDs. We consider both "general" preferences and a form of layered preferences that we call "pyramid" preferences. The properties of the class of approaches are also analyzed. In particular, we show that, when the resume and extension operations are defined such that they constitute a closed semiring, a more efficient constraint propagation algorithm can be used. Finally, we provide a preliminary implementation of the constraint propagation algorithms. Abstract : Example of a bound on differences with layered preferences representing the possible distances between points P1 and P2, and the qualitative preferences over such distances. … (more)
- Is Part Of:
- International journal of intelligent systems. Volume 36:Issue 5(2021)
- Journal:
- International journal of intelligent systems
- Issue:
- Volume 36:Issue 5(2021)
- Issue Display:
- Volume 36, Issue 5 (2021)
- Year:
- 2021
- Volume:
- 36
- Issue:
- 5
- Issue Sort Value:
- 2021-0036-0005-0000
- Page Start:
- 1998
- Page End:
- 2035
- Publication Date:
- 2021-02-13
- Subjects:
- bounds on differences -- constraint propagation -- constraints with preferences -- fuzzy information -- query answering
Artificial intelligence -- Periodicals
Expert systems (Computer science) -- Periodicals
Intelligence artificielle -- Périodiques
Systèmes experts (Informatique) -- Périodiques
006.3 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1098-111X ↗
https://www.hindawi.com/journals/ijis ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/int.22369 ↗
- Languages:
- English
- ISSNs:
- 0884-8173
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.310500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22309.xml