Title: Multiagent Planning and Scheduling

Presenter: Bradley J. Clement
           Artificial Intelligence Group
           Jet Propulsion Laboratory

Abstract:

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.  Multiagent scheduling is similar, except
the focus is less on choosing tasks and more on how and when to
perform them.  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/scheduling 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.

Basic knowledge of artificial intelligence and planning techniques
will be helpful, but not necessary. This tutorial will give
researchers and practitioners an understanding of the motivations,
applications, and history of work in multiagent planning up to present
day. After this tutorial, a graduate student could choose a thesis
topic and know how to situate it with prior work.  A research
practitioner or systems engineer would have references to relevant
research and resources to implement a multiagent planning system.