presenters:

• Bradley Clement
• Keith Decker

Multiagent planning is concerned with planning by (and for) multiple agents. It can involve agents planning for a common goal, an agent coordinating the plans or planning of others, or agents refining their own plans while negotiating over tasks or resources. Distributed continual planning addresses these problems when further complicated with interleaved execution. More than ever industry, space, and the military are seeking systems that can solve these problems.

This tutorial will describe variations of the multiagent planning problem, discuss issues in the applicability and design of multiagent planning systems, and describe some real-world multiagent planning problems. We will also review the history of research contributions to this sub-field and describe frameworks and systems such as Distributed NOAH, GPGP, DSIPE, and SHAC. In addition, we will describe open research issues in multiagent planning and its overlap and relation to other fields, such as market-based AI and game theory.

Brad Clement is a senior member of the Artificial Intelligence Group at the Jet Propulsion Laboratory in Pasadena, CA, where he is developing methods for coordinating planning and scheduling for single and multiple spacecraft/missions. He received a Ph.D. in computer science and engineering from the University of Michigan, Ann Arbor.

Keith Decker is an Associate Professor of Computer and Information Sciences at the University of Delaware, where he continues work on the DECAF agent toolkit and extending TAEMS and GPGP approaches to coordinated planning and scheduling. He received his Ph.D. in computer science from the University of Massachusetts, Amherst.