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Methods of inferring user preferences using ontologies use ontology structure based similarity and an inference mechanism in defining ontology filtering (OF). Items are recommended to users by identifying items that the users may prefer, but may not have b ...
The reason for using distributed constraint satisfaction algorithms is often to allow agents to find a solution while revealing as little as possible about their variables and constraints. So far, most algorithms for DisCSP do not guarantee privacy of this ...
We propose ODPOP, a new distributed algorithm for \textit{open multiagent combinatorial optimization} \cite{Faltings2005c}. The ODOP algorithm explores the same search space as the dynamic programming algorithm DPOP~\cite{Petcu2005} or the AND/OR search al ...
A computer implemented method is provided for monitoring the quality of service of a service provider, the method comprising the steps of receiving first and second reports from first and second clients, respectively, the first and second reports having in ...
Ontologies are being successfully used to overcome semantic heterogeneity, and are becoming fundamental elements of the Semantic Web. Recently, it has also been shown that ontologies can be used to build more accurate and more personalized recommendation s ...
We present a new hybrid algorithm for local search in distributed combinatorial optimization. This method is a mix between classical local search methods in which nodes take decisions based only on local information, and full inference methods that guarant ...
Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2007
We define the distributed continuous-time combinatorial optimization problem. We propose a new notion of solution stability in aynamic optimization, based on the cost Of change from an already-implemented solution to the new one. Change costs are modeled w ...
Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2007
In many interactive decision making scenarios there is often no solution that satisfies all of the user's preferences. The decision process can be helped by providing explanations. Relaxations show sets of consistent preferences and, thus, indicate which p ...
American Association for Artificial Intelligence, Menlo Park, CA 94025-3496, United States2007
Conversational recommenders can help users find their most preferred item among a large range of options, a task that we call preference-based search. ...
We model social choice problems in which self interested agents with private utility functions have to agree on values for a set of variables subject to side constraints. The goal is to implement the efficient solution, maximizing the total utility across ...