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.

通过开发基于 ASP 的代理体系结构和推理算法，并结合集中式推理、分散式推理、执行监控以及网络通信推理，来解决在动态环境下协调无人机团队的挑战。