Inferring threats in urban environments with uncertain and approximate data: an agent-based approach

摘要

In this article we discuss the problem of inferring threats in an urban environment, where the knowledge of the environment involves multiple types of intelligence and infrastructure data, and is by nature uncertain or approximate. We use a collection of situation-aware agents to infer potential threats in such environments, where agents are responsible for event correlation and situation assessment. We review the weaknesses of a current approach to threat assessment in Homeland Security and then describe our agent-based approach. The key innovations of our agent-based approach are: an ontological commitment to events and situations, fuzzy event correlation, fuzzy situation assessment, adaptability and learning during threat assessment operations, and an enhancement of traditional belief-desire-intention (BDI) agents with situation awareness. We describe the properties of situation-aware BDI agents and discuss the implementation of them on a variety of BDI agent platforms. Lastly, we discuss the interoperability of these platforms and address the issue of scalability through coupling to large-scale peer-to-peer overlays.