Toward the Development of a Cognitive Agent for Wide-Area Search

Abstract

We present the development of a cognitive agent for real-time, wide-area search applications. Wide-area search problems present specific challenges driven by limited resources, large search areas, and limited time to conduct a search or inspection. Cognitive agents present an opportunity to incorporate a range of reasoning and sensor processing approaches to more effectively focus attention and make decisions about how to interpret data.We developed a design for a cognitive agent and implemented supporting reasoning algorithms to interact with sensor data. The agent encodes knowledge about objects of interest, and how they present themselves in the environment. This allows object detection algorithms to focus on detecting single objects, keeping training data requirements manageable. The cognitive agent provides external reasoning to reduce false alarm rates and make additional inferences. In this paper, we describe the cognitive agent design, conduct feasibility studies to establish reasoning strategies, and identify areas for future agent contributions.