Matthew Gillen, Arvind Lakshmikumar, David Chelberg,
Cynthia Marling,
Mark Tomko and Lonnie Welch
School of Electrical
Engineering and Computer Science
Ohio University, Athens, OH 45701
USA
Artificial Intelligence (AI) algorithms for planning in non-trivial domains are typically resource-intensive. We believe that a framework for developing planning algorithms that allows an arbitrary level of decomposition and provides the means for distributing the computation would be a valuable contribution to the AI community.
We propose a general, flexible, and scalable hierarchical architecture for designing multi-agent distributed systems. We developed this architecture to facilitate the development of software for soccer-playing robots. These robots will compete in the international robot soccer competition RoboCup. All of our software, from the high-level team strategy planning down to the control loop for the motors on our robots fits into this architecture.
We build on the notion of deliberative and reactive agents, forming a hierarchy of hybrid agents. The hierarchy covers the entire continuum of hybrid agents: agents near the root of the hierarchy are mostly deliberative, while agents near the leaves are almost purely reactive.