Overview of AIPS'02 Program

Tuesday 23/04

Wednesday 24/04

Thursday 25/04

Friday 26/04

Saturday 27/04

AIPS Technical Conference
WS-Tu1: Planning and Scheduling using Multiple Criteria WS-We1: Knowledge Engineering Tools and Techniques for AI Planning
WS-Tu2: Planning via Model Checking WS-We2: Planning for Temporal Domains
WS- Tu3: Is There Life Beyond Operator Sequencing? -- Exploring Real World Planning WS-We3: On-line Planning and Scheduling
TUT-Tu1: Greedy On-line Planning. (AM)
TUT-Tu2: Constraint-Based Scheduling in an A.I. Planning and Scheduling Perspective. (PM)
TUT-We1: Planning as Model Checking.

Planning Competition

Overview of the various events colocated with AIPS'02

Friday 19/04

Saturday 20/04

Sunday 21/04

Monday 22/04

Tuesday 23/04

Wednesday 24/04

Thursday 25/04

Friday 26/04

Saturday 27/04


Planning Competition

AIPS Workshops

AIPS Tutorials

AIPS Technical Conference

KR Technical Conference

KR Workshops


Best Paper Awards

The AIPS'02 Chairs are happy to announce that the two papers :
A knowledge-based approach to planning with incomplete information and sensing. R.P.A. Petrick and F.Bacchus (session 1)
Planning for distributed execution through use of probabilistic opponent models. P.Riley and M.Veloso (session 10)
received AIPS'02 Best Paper Awards

Invited Speakers

Bernhard Nebel (AIPS/KR Joint invited speaker , Thursday, 25th)

The philosophical soccer player

The main task of a soccer player is to score goals. However, there are moments in life when questions like the following become relevant: Is the ball I am seeing a hallucination or is it real? Should I revise my beliefs about where the ball is? And if so, what is the next action I should execute? Would this action be to the benefit of my team? In the talk I will address these questions and show how one can create a successful robotic soccer team by giving the right answers.

Bernhard Nebel received his Ph.D. (Dr. rer. nat.) from the University of Saarland in 1989. From 1993 to 1996 he held an Associate Professor position (C3) at the University of Ulm. Since 1996 he is Professor at Albert-Ludwigs-Universität Freiburg. Among other professional services, he served as the Program Co-chair for the 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR'92) and as the Program Chair for the 17th International Joint Conference on Artificial Intelligence (IJCAI'01). In addition, he is a member of the editorial boards of Artificial Intelligence and AI Communication and he is the Research Note editor of Artificial Intelligence. His main research interests are knowledge representation and reasoning, planning, and robotics with an emphasis on robotic soccer.

Jan Karel Lenstra (Friday, 26th)

Local search in combinatorial optimization

Combinatorial optimization is the discipline of decision making in the case of discrete alternatives. In the past 25 years, the area has been subject to significant progress on at least three fronts. Advances in linear programming and polyhedral techniques have enourmously extended the realm of methods that are guaranteed to find optimal solutions. The theory of design and analysis of algorithms has taught us a lot about performance bounds that can ­ or probably cannot ­ be met in polynomial time. And there has been a surge in the development of heuristics solution approaches, which come under the general heading of local search. I will review these developments, emphasizing developments in local search.

Jan Karel Lenstra was researcher at CWI in Amsterdam from 1969 until 1989 and has been Professor of Optimization at the Technische Universiteit Eindhoven since 1989. His research interests are in combinatorial optimization, in particular complexity, approximation, routing, and scheduling. He has been chair of the Mathematical Programming Society, editor-in-chief of Mathematics of Operations Research, and chair of the Wiskundig Genootschap (the Dutch Mathematical Society). He is presently Dean of the Department of Mathematics and Computer Science in Eindhoven.

Martha Pollack (Saturday, 27th)

Plan-Management Assistants: From Homework Helpers to Cognitive Orthotics

Much of the work in AI planning has been in the context of autonomous-agent design: the goal is to develop algorithms and heuristics that can be used by autonomous systems that need to plan their actions. In this talk, I will describe an alternative use for planning technology: helping people manage their plans. I will describe how techniques developed in the planning community-including methods for plan generation, plan recognition, and execution monitoring-can be integrated with one another and with techniques from other areas, such as workflow management, to build a variety of plan-management assistants. Potential users of such systems range from schoolchildren learning to manage their homework assignments, to adults using smart PDAs to manage their work activities, to elderly people with memory decline using cognitive orthotics to help manage their activities of daily living. I will provide examples of such systems, including Autominder, a cognitive orthotic for the elderly being developed in my research group.

Martha E. Pollack is Professor of Computer Science and Engineering at the University of Michigan. She was previously a Professor at the University of Pittsburgh, and a Senior Computer Scientist at SRI International. Pollack, who received her Ph.D. from the University of Pennsylvania, is a Fellow of the AAAI; amongst her other honors is the Computers and Thought Award (1991). She is currently serving as Executive Editor of the Journal of Artificial Intelligence Research. Her research interests are in plan generation, plan management, temporal reasoning, computational models of rationality, and assistive technology for cognitive impairment.

List of accepted papers

107 Structure and Complexity in Planning with Unary Operators Domshlak Carmel,Department of Computer Science
Ronen Brafman; Ben-Gurion University of the Negev
112 On Control Knowledge Acquisition by Exploiting Human-Computer Interaction Aler, Ricardo, Universidad Carlos III de Madrid
Daniel Borrajo, Universidad Carlos III de Madrid,
114 Symbolic Pattern Databases in Heuristic Search Planning Edelkamp, Stefan,Computer Science Institut;
115 The FAR-OFF system: A Heuristic Search Case-Based Planning Tonidandel, Flavio,University of Sao Paulo
Marcio Rillo ; University of Sao Paulo
118 Plan Representation for Robotic Agents Beetz, Michael, K,Department of Computer Science IX
124 Local Search Topology in Planning Benchmarks: A Theoretical Analysis Hoffmann, Joerg,University Freiburg;
130 Extending the Exploitation of Symmetries in Planning Fox, Maria,University of Durham, UK
Derek Long ; University of Durham
131 Filtering Algorithms for Batch Processing with Sequence Dependent Setup Times Vilim, Petr,Charles University;
Bartak, Roman ; Charles University;
134 Execution Monitoring with Quantitative Temporal Dynamic Bayesian Networks Colbry, Dirk, J,University of Michigan
Bart Peintner; University of Michigan
Martha E. Pollack,University of Michigan
135 Applying Domain Analysis Techniques for Domain-Dependent Control in TALplanner Kvarnström, Jonas,Linköping University, Sweden
137 Universal Quantification in a Constraint-Based Planner Golden, Keith,NASA Ames Research Center
Jeremy Frank; NASA Ames Research Center
138 A Plan-Based Personalized Cognitive Orthotic McCarthy, Colleen E,University of Pittsburgh
Martha Pollack; University of Michigan
139 Decidability and Undecidability Results for Planning with Numerical State Variables Helmert, Malte,Albert-Ludwigs-Universitaet Freiburg;
143 An Interactive Method for Inducing Operator Descriptions McCluskey, T, L,School of Computing and Mathematics;
Richardson,N,E ; The University of Huddersfield
Simpson,R,M ; The University of Huddersfield
146 Active Coordination of Distributed Human Planners Myers, Karen, L.,Artificial Intelligence Center
Peter A. Jarvis, SRI International
Thomas J. Lee, SRI International,
149 CaMeL: Learning Methods for HTN Planning Okhtay Ilghami,University of Maryland
Dana Nau ; University of Maryland
Hector Munoz-Avila ; Lehigh University
David Aha ; Naval Research Laboratory
152 On the Role of Ground Actions in Refinement Planning Younes, Hakan, L,Carnegie Mellon University
Reid Simmons; Carnegie Mellon University
153 Estimated-Regression Planning for Interactions with Web Services McDermott, Drew V.,Yale University;
155 Faster Probabilistic Planning Through More Efficient Stochastic Satisfiability Problem Encodings Majercik, Stephen M.,Bowdoin College
Andrew P. Rusczek ; Bowdoin College
157 Speculative Execution for Information Gathering Plans Barish, Greg,University of Southern California / Information Sciences Institute
Craig A. Knoblock; University of Southern California / Information Sciences Institute
164 Fragment-based Conformant Planning Kurien, James A,Xerox Palo Alto Research Center
P. Pandurang Nayak; Stratify, Inc.
David E. Smith; NASA Ames Research Center
166 Improving Heuristics for Planning as Search in Belief Space Bertoli, Piergiorgio,IRST - Istituto per la Ricerca Scientifica e Tecnologica
Alessandro Cimatti; IRST
169 LPG: A Planner Based on Local Search for Planning Graphs with Action Costs Gerevini, Alfonso,Università di Brescia, Dipartimento di Elettronica per l'Automazione
Ivan Serina; DEA, Università di Brescia
170 On the Identification and Use of Hierarchical Resources in Planning and Scheduling Bernd Schattenberg,Dept. of Artificial Intelligence
Susanne Biundo; Dept. of Artificial Intelligence, University of Ulm
172 Constraint model-based planning and scheduling with multiple resources and complex collaboration schema Jean-Clair Poncet,Axlog Ingénierie
Guettier Christophe ; Xerox Palo Alto Research Center Bertand Allo ; Axlog Ingénierie
Vincent Legendre ; Axlog Ingénierie
Nelly Strady-Lécubin ; Axlog Ingénierire
175 Partially Observable Planning as Backward Search with BDDs Rintanen, Jussi, T,Albert-Ludwigs-Universität Freiburg
181 Analyzing Plans with Conditional Effects Winner, Elly,Computer Science Department
Manuela Veloso; Computer Science Department, Carnegie Mellon University
183 Planning for Distributed Execution Through Use of Riley, Patrick F.,Computer Science Department
Manuela Veloso ; Carnegie Mellon University
186 The Logic of Reachability Smith, David E.,NASA Ames Research Center;
Ari Jonsson ; RIACS
187 Heuristic Search-Based Replanning Koenig, Sven,College of Computing, Georgia Institute of Technology
David Furcy; Georgia Institute of Technology
Colin Bauer; Georgia Institute of Technology
188 A Knowledge-Based Approach to Planning with Incomplete Information and Sensing Bacchus, Fahiem,University of Toronto
Ronald Petrick ; University of Toronto
190 Planning Graph-based Heuristics for Cost-sensitive Temporal Planning Do, Minh B.,Arizona State University, The United States
Subbarao Kambhampati; Arizona State University

Social Events


Visit of Historical Toulouse on the 28th morning

AIPS'02 is happy to offer to AIPS participants and accompanying persons a guided (English) pedestrian visit of Toulouse downtown. The visit will start around 10:00 near the Toulouse tourism office (Place du Donjon) and last two hours.

The visit is offered by AIPS but registration is required. If you are interested in joining the visit, please send an e-mail to Jackie Som and specify the name of the persons coming, or register at the registration desk during the conference..

Comments on the WEB site to : Félix Ingrand

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