This paper puts forward a normative framework for computational societies which enables the handling of incomplete knowledge about normative relations. In particular, attempts to p...
Multiagent Inductive Learning is the problem that groups of agents face when they want to perform inductive learning, but the data of interest is distributed among them. This pape...
This paper presents a framework for providing dynamically deployable services in ubiquitous computing settings. The goal of the framework is to provide people, places, and objects ...
Abstract. We study the problem of predictive data mining in the competitive multi-agent setting, in which each agent is assumed to have some partial knowledge needed for correctly ...
Abstract. Logic-based argumentation offers an approach to querying and revising multiple ontologies that are inconsistent or incoherent. A common assumption for logic-based argumen...