Preference Reasoning

2005 ◽  
pp. 9-12 ◽  
Author(s):  
Francesca Rossi
Keyword(s):  
Preference Reasoning

Preference reasoning with soft constraints in constraint-based recommender systems

Constraints ◽  
2010 ◽  
Vol 15 (4) ◽  
pp. 574-595 ◽  
Author(s):  
Markus Zanker ◽  
Markus Jessenitschnig ◽  
Wolfgang Schmid
Keyword(s):  
Recommender Systems ◽  
Soft Constraints ◽  
Preference Reasoning

scholarly journals Reasoning about social preferences with uncertain beliefs

2021 ◽  
Author(s):  
isaac davis ◽  
Ryan W. Carlson ◽  
Yarrow Dunham ◽  
Julian Jara-Ettinger
Keyword(s):  
Expected Utility ◽  
Utility Maximization ◽  
Social Preference ◽  
Social Preferences ◽  
Social Judgments ◽  
Social Agents ◽  
Preference Reasoning ◽  
The Face ◽  
Expected Utility Maximization ◽  
Social Uncertainty

We propose a computational model of social preference judgments that accounts for the degree of an agents’ uncertainty about the preferences of others. Underlying this model is the principle that, in the face of social uncertainty, people interpret social agents’ behavior under an assumption of expected utility maximization. We evaluate our model in two experiments which each test a different kind of social preference reasoning: predicting social choices given information about social preferences, and inferring social preferences after observing social choices. The results support our model and highlight how un- certainty influences our social judgments.

scholarly journals Implementation of Preference Reasoning by Manipulating Logical Chain

2006 ◽  
Vol 17 (12) ◽  
pp. 2518
Author(s):  
Zhi-Zheng ZHANG
Keyword(s):  
Preference Reasoning

scholarly journals What’s Wrong with “You Say You’re Happy, but . . . ” Reasoning?

2019 ◽  
pp. 309-325
Author(s):  
Jason Marsh
Keyword(s):  
Lived Experience ◽  
Well Being ◽  
Disabled People ◽  
Preference Reasoning ◽  
Moral Risk ◽  
Testimonial Injustice ◽  
Adaptive Preference

Disability-positive philosophers often note a troubling tendency to dismiss what disabled people say about their well-being. This chapter seeks to get clearer on why this tendency might be troubling. It argues that recent appeals to lived experience, testimonial injustice, and certain challenges to adaptive-preference reasoning do not fully explain what is wrong with questioning the happiness of disabled people. It then argues that common attempts to debunk the claim that disabled people are happy are worrisome because they threaten everyone’s well-being and are further challenged by an argument from moral risk.

An introduction to reasoning over qualitative multi-attribute preferences

2015 ◽  
Vol 30 (3) ◽  
pp. 342-372 ◽  
Author(s):  
Ingrid Nunes ◽  
Simon Miles ◽  
Michael Luck ◽  
Carlos J. P. Lucena
Keyword(s):  
Artificial Intelligence ◽  
Research Areas ◽  
Preference Reasoning ◽  
The Way ◽  
Qualitative Preferences

AbstractResearch on preferences has significantly increased in recent years, as it involves not only many subproblems to be investigated, such as elicitation, representation, and reasoning, but has also been the target of different research areas, for example, artificial intelligence and databases. In particular, much work has focused on qualitative preferences, because these are closer to the way people express their preferences in comparison with quantitative preferences. Against this background, a large number of approaches have been proposed, associated with heterogeneous areas, so that these approaches are usually just compared with those of the same area. In response, we present in this paper a survey of approaches toqualitative multi-attribute preference reasoning, covering different research areas. We introduce selected approaches that propose different techniques and algorithms, which take as input qualitative multi-attribute preference statements following a particular structure specified by the approach. We analyse each approach in a systematic way and discuss their commonalities and limitations.

scholarly journals Complexity Results in Optimistic/Pessimistic Preference Reasoning

2016 ◽  
Author(s):  
Christian Bessiere ◽  
Remi Coletta ◽  
Gaelle Hisler ◽  
Anastasia Paparrizou
Keyword(s):  
Preference Reasoning ◽  
Complexity Results

Advanced P-Tree based K-Nearest neighbors for customer preference reasoning analysis

2008 ◽  
Vol 20 (5) ◽  
pp. 569-579 ◽  
Author(s):  
Xiang Li ◽  
Daming Shi ◽  
Varoon Charastrakul ◽  
Junhong Zhou
Keyword(s):  
Nearest Neighbors ◽  
K Nearest Neighbors ◽  
Customer Preference ◽  
Preference Reasoning

scholarly journals Closing the Loop: Bringing Humans into Empirical Computational Social Choice and Preference Reasoning

2020 ◽  
Author(s):  
Nicholas Mattei
Keyword(s):  
Social Choice ◽  
Complexity Analysis ◽  
Human Interaction ◽  
Computational Social Choice ◽  
Preference Reasoning ◽  
Equal Importance ◽  
Algorithms And Complexity ◽  
Computer Scientists ◽  
Closing The Loop ◽  
Tools And Techniques

Research in both computational social choice and preference reasoning uses tools and techniques from computer science, generally algorithms and complexity analysis, to examine topics in group decision making. This has brought tremendous progress in the last decades, creating new avenues for research and results in areas including voting and resource allocation. I argue that of equal importance to the theoretical results are impacts in research and development from the empirical part of the computer scientists toolkit: data, system building, and human interaction. I highlight work by myself and others to establish data driven, application driven research in the computational social choice and preference reasoning areas. Along the way, I highlight interesting application domains and important results from the community in driving this area to make concrete, real-world impact.

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