Nested Preferences in Answer Set Programming
Fundamenta Informaticae - Latin American Workshop on Logic Languages, Algorithms and New Methods of Reasoning (LANMR)
Dealing with explicit preferences and uncertainty in answer set programming
Annals of Mathematics and Artificial Intelligence
Conditional preference nets and possibilistic logic
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Skyline queries, front and back
ACM SIGMOD Record
Strong equivalence of qualitative optimization problems
Journal of Artificial Intelligence Research
Editorial: Preference learning and ranking
Machine Learning
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Preferences are useful in many real-life problems, guiding human decision making from early childhood up to complex professional and organizational decisions. In artificial intelligence specifically, preferences is a relatively new topic of relevance to nonmonotonic reasoning, multiagent systems, constraint satisfaction, decision making, social choice theory and decision-theoretic planningThe first part of this book deals with preference representation, with specific chapters dedicated to representation languages, nonmonotonic logics of preferences, conditional preference networks, positive and negative preferences, and the study of preferences in cognitive psychology. The second part of the book deals with reasoning with preferences, and includes chapters dedicated to preference-based argumentation, preferences database queries, and rank-ordering outcomes and intervals. The author concludes by examining forthcoming research perspectives.This is inherently a multidisciplinary topic and this book will be of interest to computer scientists, economists, operations researchers, mathematicians, logicians, philosophers and psychologists.