Traditional AI reasoning techniques have been used successfully in many domains, including logistics, scheduling and game playing. This paper is part of a project aimed at investigating how such techniques can be extended to coordinate teams of unmanned aerial vehicles (UAVs) in dynamic environments. Specifically challenging are real-world environments where UAVs and other network-enabled devices must communicate to coordinate -- and communication actions are neither reliable nor free. Such network-centric environments are common in military, public safety and commercial applications, yet most research (even multi-agent planning) usually takes communications among distributed agents as a given. We address this challenge by developing an agent architecture and reasoning algorithms based on Answer Set Programming (ASP). Although ASP has been used successfully in a number of applications, to the best of our knowledge this is the first practical application of a complete ASP-based agent architecture. It is also the first practical application of ASP involving a combination of centralized reasoning, decentralized reasoning, execution monitoring, and reasoning about network communications.
As methods for detecting improvised explosive devices (IEDs) continue to diversify, it becomes increasingly important to establish a framework for coordinating distributed IED monitoring resources to best protect a designated area. The purpose of this paper is to establish the beginnings of such a framework in a distributed plan execution context. The first contribution of this paper is defining an automated planning domain for distributed IED detection. In doing so, we investigate approaches for coordinating distributed plan execution resources. Whereas many existing multi-agent system (MAS) frameworks abstract network information from agent decision-making processes, we instead propose that MAS frameworks consider network properties to improve effectiveness. The second contribution of the paper is the description of several types of network-aware planning, execution, and monitoring agents and a comparison of their performance and effectiveness in an IED monitoring scenario. The results of this research ...