My research is focused on knowledge representation and reasoning, especially, preference modeling, learning and reasoning, and computational social choice. Preference modeling, learning and reasoning is a major research area in artificial intelligence (AI) and decision theory, and is closely related to the social choice theory considered by economists and political scientists. In my research I explore emerging connections between preferences in AI and social choice theory. My main focus is on qualitative preference representation languages extending and combining formalisms such as lexicographic preference trees (LP-trees) [1], answer-set optimization theories (ASO-theories) [3], possibilistic logic [4]; and conditional preference networks (CP-nets) [2], on learning problems that aim at discovering qualitative preference models and predictive preference information from empirical data; and on qualitative preference reasoning problems centered around preference optimization and strategy-proofness of preference aggregation methods. Applications of my research include recommendation systems, decision support tools, multi-agent systems, and Internet trading and marketing platforms.
展开▼
