An inference sharing architecture for a more efficient context reasoning

In this paper we describe a distributed peer-to-peer agent architecture of context consumers and context providers. The objective of this architecture is to split the context reasoning problem into smaller parts in order to reduce the inference time. We describe how this inference sharing process works, partitioning the context information according to the interests of the agents, location and a certainty factor. We also discuss the system architecture, analyzing the negotiation process between the agents.