Semantic Memory for Pervasive Architecture

Abstract

Pervasive environments become a reality and involve a large variety of networking smart devices. This ambient intelligence tends to complex interactions. Lots of researches have been done on intelligent and reactive architectures able to manage multiple events and act in the environment. In the Robotics domain, a decision process must be implemented in the robot brain or a collective intelligence to accomplish the multimodal interaction with humans in human environment. We present a semantic agents architecture giving the robot and other entities the ability to well understand what is happening and thus provide more robust processing. We will describe our agent memory. Intelligence and knowledge about objects in the environment is stored in two ontologies linked to a reasoner an inference engine. To share and exchange information, an event knowledge representation language is used by semantic agents. This pervasive architecture brings other advantages: cooperation, redundancy, adaptability, interoperability and platforms independent.