Defeasible Contextual Reasoning with Arguments in Ambient Intelligence

Abstract—The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities that possess and share the available context information render contextual reasoning a very challenging task. The accomplishment of this task requires formal models that handle the involved entities as autonomous logic-based agents and provide methods for handling the imperfect and distributed nature of context. This paper proposes a solution based on the MultiContext Systems paradigm, in which local context knowledge of ambient agents is encoded in rule theories (contexts), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To handle imperfect context, we extend Multi-Context Systems with nonmonotonic features; local defeasible theories, defeasible mapping rules, and a preference ordering on the system contexts. On top of this model, we have developed an argumentation framework that explo...

• Type: Journal
• Year: 2010
• Where: TKDE
• Authors: Antonis Bikakis, Grigoris Antoniou
• Keywords: Ambient Agents, Context Information Render, Mapping Rules, TKDE 2010