Learning of Hierarchical Task Network Domain Descriptions: Theory and Empirical Results

Speaker:	Professor Hector MUNOZ-AVILA
		Department of Computer Science and Engineering
		Lehigh University

Title:		"Learning of Hierarchical Task Network Domain
		 Descriptions: Theory and Empirical Results"

Date:		Tuesday, 13 May 2008

Time:		11:00am - 12noon

Venue:		Lecture Theatre H
		(Chen Kuan Cheng Forum, near lift nos. 27/28)
		HKUST

Abstract:

Interest in hierarchical task network (HTN) planning has been recurrent
over the years primarily because many real-world domains are amenable to
hierarchical representations, including military planning, strategy
formulation in computer games, manufacturing processes, project
management, and story-telling. Despite this interest, a major hurdle for
using HTN planning is the need for HTN domain descriptions. Frequently, it
is assumed that this domain description is given and research has
concentrated in developing reasoning mechanisms using this knowledge to
solve new problems. In this talk I present algorithms for learning the
hierarchical structure and preconditions of HTN domain descriptions from
an input consisting of classical planning problems in a planning domain
and solutions to those problems, as well as some additional information.
We analyse theoretical properties of these algorithms. Our theoretical
results demonstrate that our algorithms can converge to a complete domain
description. We present a number of experiments confirming our theoretical
results.

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Biography:

Dr. Hector MUNOZ-AVILA is an associate professor at the Department of
Computer Science and Engineering at Lehigh University. DR. MUNOZ-AVILA has
done extensive research on case-based reasoning, planning, and machine
learning. He is also conducting research in advancing Game AI with AI
techniques. DR. MUNOZ-AVILA is recipient of a National Science Foundation
(NSF) CAREER award (2007) and two papers awards. He currently holds a
Lehigh Class of 1961 Professorship. He has been chair for various
international scientific meetings including the Sixth International
Conference on Case-Based Reasoning (ICCBR-05). DR. MUNOZ-AVILA is
currently funded by the National Science Foundation (NSF) and the Defense
Advanced Research Projects Agency (DARPA). He has been funded in the past
by the Defense Advanced Research Projects Agency (DARPA), the Office of
Naval Research (ONR), and the Naval Research Laboratory (NRL).