21st International Conference on Automated Planning and Scheduling

Adventium Labs ATRiCS Advanced Traffic Solutions

Robert Bosch GmbH European Coordinating Committee for Artificial

Intelligence (ECCAI)

European Space Agency (ESA) Florida Institute for Human & Machine Cognition

SICK AG SIFT

Artificial Intelligence Journal

David E. Smith Deutsche Forschungs-gemeinschaft (DFG)

European Office of Aerospace Research &

Development

IBM Research

Institute for Computational

Sustainability (ICS)

National ICT Australia Limited

National Science Foundation (NSF)

TRACLabs Inc. University of Freiburg

Conference ProgramJune 11-16, 2011

Freiburg, Germany

VENUE OF SATELLITE EVENTS

The satellite program (doctorial consortium, workshops and tu-torials) will be hosted at

Building 101Computer Science CampusGeorges-Köhler-Allee 10179110 Freiburg

Map data © OpenStreetMap contributors, CC-BY-SA; rendering rules by Frederik Ramm and Jochen Topf

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CONTENTS

Organizing CommitteeAwardsInvited SpeakersWorkshopsTutorialsMain Conference ProgramSystem Demonstrations & DC PostersSocial ProgramGeneral InformationSatellite Events at a GlanceMain Conference at a Glance

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17212831323334

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ORGANIZING COMMITTEE

Conference ChairsMalte Helmert (University of Freiburg, Germany)Stefan Edelkamp (University of Bremen, Germany)

Program Chairs Fahiem Bacchus (University of Toronto, Canada)Carmel Domshlak (Technion, Israel)

Local Arrangement Gabriele Röger (University of Freiburg, Germany)

Workshop Chairs Blai Bonet (Universidad Simón Bolívar, Venezuela)Amedeo Cesta (Institute for Cognitive Science and Technology, Italy)

Tutorial Chairs Stephen Smith (Carnegie Mellon University, USA)Rong Zhou (Palo Alto Research Center, USA)

System Demonstration Chairs Piergiorgio Bertoli (Istituto Trentino di Cultura, Italy)Minh Do (Palo Alto Research Center, USA)

Doctoral Consortium ChairsHéctor Geffner (Universitat Pompeu Fabra, Spain)Patrik Haslum (Australian National University, Australia)Subbarao Kambhampati (Arizona State University, USA)

Sponsorship Chairs Jeremy Frank (NASA Ames Research Center, USA)Bernhard Nebel (University of Freiburg, Germany)

Industry Liaisons Ari Jónsson (Reykjavik University, Iceland)Jana Koehler (IBM Research, Switzerland)

LOCAL SUPPORT

kongress & kommunikation gGmbHKatja Lemke

VolunteersYusra AlkhazrajiManuela OrtliebSilvan SieversTiago Stegun Vaquero

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ICAPS 2011 AWARDS

Best Paper AwardAutomatic Construction of Efficient Multiple Battery Usage PoliciesMaria Fox, Derek Long, Daniele Magazzeni

Best Student Paper AwardPlanning to Perceive: Exploiting Mobility For Robust Object DetectionJavier Velez, Garrett Hemann, Albert S. Huang, Ingmar Posner, Nicholas Roy

Computing All-Pairs Shortest Paths by Leveraging Low TreewidthLéon Planken, Mathijs de Weerdt, Roman van der Krogt(Honorable Mention)

Trade-Offs in Sampling-Based Adversarial PlanningRaghuram Ramanujan, Bart Selman(Honorable Mention)

Influential Paper AwardAlgorithms for Propagating Resource Constraints in AI Planning and Scheduling: Existing Approaches and New ResultsPhilippe Laborie, ECP 2001

Best Dissertation AwardImplicit Abstraction Heuristics for Cost-Optimal PlanningMichael Katz

Effective Search Techniques for Non-Classical Planning via ReformulationJorge Baier(Honorable Mention)

Foundations and Applications of Generalized PlanningSiddharth Srivastava(Honorable Mention)

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INVITED SPEAKERS

Abstract: Spoken dialog systems present a clas-sic example of planning under uncertainty. In a spoken dialog system, a computer is trying to help a person accomplish something, using spoken language as the communication medi-um. A key challenge is that speech recognition er-rors are ubiquitous and impossible to detect reliably, so the state of the conversation can nev-er be known with certainty. Another challenge is that people do not behave deterministically. Des-pite these challenges, the system must choose actions to make progress to a long term goal. As such, decision theory presents an attractive ap-proach to building spoken dialog systems. Initial work on “toy” dialog systems validated benefits, but also found that straightforward formulations could not scale to real-world problems. Sub-sequent work by a number of research teams has shown how to scale to industrial-scale sys-tems, how to incorporate high-fidelity user simu-lations, and how to synthesize commercial development practices with automatic optimiza-tion. This talk traces the evolution of this applica-

tion of planning under uncertainty, comments on progress toward use in industry, and suggests fu-ture avenues of research relevant to researchers interested in planning under uncertainty.

Bio: Jason Williams is Principal Member of Tech-nical Staff at AT&T Labs – Research. His research interests include spoken dialog systems, plan-ning under uncertainty, spoken language under-standing, and speech recognition. He is on the Scientific Committee of SigDial (the Special In-terest Group on Dialog and Discourse), is an elec-ted member of the IEEE Speech and Language Technical Committee (SLTC), and is on the board of directors of the Association for Voice Interac-tion Design (AVIxD). Jason holds a PhD and Mas-ters in Speech and Language Processing from Cambridge University (UK), and a BSE in Electric-al Engineering from Princeton University (USA). Before joining AT&T Labs, he held positions in in-dustry where he built spoken dialog systems which have since fielded millions of phone calls.

Jason D. WilliamsSpoken Dialog Systems as an Application of Planning under UncertaintyTuesday, June 14, 2011, 09:00–10:00

Abstract: Every year, natural disasters cause infrastructure damages and power outages that have considerable impacts on both quality of life and economic welfare. Mitigating the effects of disasters is an important but challenging task, given the underlying uncertainty, the need for fast response, and the complexity and scale of the infrastructures involved, not to mention the social and policy issues. This talk describes how to use planning and scheduling technologies to address these challenges in a rigorous and principled way. In particular, we present the first optimization solutions to last-mile disaster preparedness and recovery for a single commodity (e.g., water) and for the electrical power network. The optimization algorithms were compared to existing practice on disaster scenarios based on the U.S. infrastructure (at

the state scale) and generated by state-of-the-art hurricane simulation tools. Some of our algorithms are deployed as part of the Los Alamos National Laboratories operational tools and provide recommendations to the U.S. Department of Homeland Security.

Bio: Pascal Van Hentenryck is a Professor of Computer Science at Brown University. He is a fellow of the Association for the Advancement of Artificial Intelligence, the recipient of the 2002 ICS INFORMS award, the 2006 ACP Award, an honorary degree from the University of Louvain, and the Philip J. Bray award for teaching excellence. He is the author of five MIT Press books and most of his research in optimization software systems has been commercialized and is widely used in academia and industry.

Pascal Van HentenryckLast-Mile Disaster Preparedness and RecoveryWednesday, June 15, 2011, 09:00–10:00

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Abstract: The games agents play – in markets, conflicts, or most other contexts – often defy strict game-theoretic analysis. Games may be un-manageably large (combinatorial or infinite state or action spaces), and present severely imper-fect information, which could be further complic-ated by partial dynamic revelation. Moreover, the game may be specified procedurally, for in-stance by a simulator, rather than in an explicit game form.

With colleagues and students over the past few years, I have been developing a body of tech-niques for strategic analysis, adopting the game-theoretic framework but employing it in domains where direct “model-and-solve” cannot apply. This empirical game-theoretic methodology em-braces simulation, approximation, statistics and learning, and search. Through applications to ca-nonical auction games, and rich trading scenari-os, we demonstrate the value of empirical methods for extending the scope of game-theoret-ic analysis. This perspective also sheds insight in-to behavioral models and bases for predicting joint action in complex multiagent scenarios.

Bio: Michael P. Wellman is Professor of Computer Science & Engineering at the University of Michigan. He received a PhD from the Massachu-setts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and de-cision-theoretic planning. From 1988 to 1992, Wellman conducted research in these areas at the USAF’s Wright Laboratory. For the past 18+ years, his research has focused on computation-al market mechanisms for distributed decision making and electronic commerce. As Chief Mar-ket Technologist for TradingDynamics, Inc. (now part of Ariba), he designed configurable auction technology for dynamic business-to-business commerce. Wellman previously served as Chair of the ACM Special Interest Group on Electronic Commerce (SIGecom), and as Executive Editor of the Journal of Artificial Intelligence Research. He is a Fellow of the Association for the Advance-ment of Artificial Intelligence and the Association for Computing Machinery.

Michael P. WellmanEmpirical Game-Theoretic Analysis and the Behavior of Software AgentsThursday, June 16, 2011, 09:00–10:00

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WORKSHOPS

Sunday, June 12, 2011

Monday, June 13, 2011

All workshops are held in building 101 on the computer science campus.

Heuristics for Domain-independent Planning (HDIP)Hall 101-00-026

Goal, Activity and Plan Recognition (GAPRec)Hall 101-01-009/013

Knowledge Engineering for Planning and Scheduling (KEPS)Hall 101-00-036

Monte-Carlo Tree Search: Theory and Applications (MCTS)Hall 101-00-010/014

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Verification and Validation of Planning and Scheduling Systems(VVPS)Hall 101-01-009/013

Planning and Learning (PAL)Hall 101-00-026

Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS)Hall 101-00-010/014

Scheduling and Planning Applications woRKshop (SPARK)Hall 101-00-036

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Heuristics for Domain-independent Planning(HDIP)

Welcome

Heuristics I

09:00–09:30 Heuristics with Choice Variables: Bridging the Gap between Planning and Graphical Models

Emil Keyder, Miquel Ramirez, Hector Geffner

09:30–10:00 Landmark-Aware Strategies for Hierarchical PlanningMohamed Elkawkagy, Pascal Bercher, Bernd Schattenberg, Susanne Biundo

Coffee Break

08:50–09:00

10:00–10:30 Computing Perfect Heuristics in Polynomial Time: On Bisimulation and Merge-and-Shrink Abstractions in Optimal Planning

Raz Nissim, Jörg Hoffmann, Malte Helmert

Organizers: Alan Fern, Patrik Haslum, Jörg Hoffmann, Michael KatzDate and Location: June 12, 2011, Hall 101-00-026 Computer Science Campus

Heuristics II

11:00–11:30 Incremental Lower Bounds for Additive Cost Planning ProblemsPatrik Haslum, John Slaney, Sylvie Thiebaux

Lunch Break

Search I

14:00–14:30 Living on the Edge: Safe Search with Unsafe HeuristicsErez Karpas, Carmel Domshlak

15:00–15:30 Cost Based Satisficing Search Considered HarmfulWilliam Cushing, J. Benton, Subbarao Kambhampati

Coffee Break

Search II

16:30–17:00 Exploiting Problem Symmetries in State-Based PlannersNir Pochter, Aviv Zohar, Jeffrey Rosenschein

17:00–17:30 On Satisficing Planning with Admissible HeuristicsRoei Bahumi, Carmel Domshlak, Michael Katz

16:00–16:30 Planning with SAT, Admissible Heuristics and A*Jussi Rintanen

11:30–12:30 Invited Talk: Learning Search HeuristicsAlan Fern

14:30–15:00 Enhancing Search for Satisficing Temporal Planning with Objective-driven DecisionsJ. Benton, Patrick Eyerich, Subbarao Kambhampati

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Poster and Demo Session16:00–17:30

09:15–09:40

Knowledge Engineering for Planning and Scheduling (KEPS)

Welcome

Oral Presentations

A Brief Review of Tools and Methods for Knowledge Engineering for Planning & Scheduling

Tiago Stegun Vaquero, José Reinaldo Silva, J. Christopher Beck

09:40–10:05 Acquisition and Re-use of Plan Evaluation Rationales on Post-DesignTiago Stegun Vaquero, José Reinaldo Silva, J. Christopher Beck

Coffee Break

09:00–09:15

10:05–10:30 The Challenge of Grounding Planning in Simulation in an Interactive Model Development Environment

Bradley J. Clement, Jeremy D. Frank, John M. Chachere, Tristan B. Smith, Keith Swanson

Organizers: Roman Barták, Simone Fratini, Lee McCluskey, Tiago Stegun VaqueroDate and Location: June 12, 2011, Hall 101-00-036 Computer Science Campus

Oral Presentations

12:15–12:40 Heuristic Search-Based Planning for Graph Transformation SystemsH.-Christian Estler, Heike Wehrheim

Lunch Break

Coffee Break

11:25–11:50 Using Planning Domain Features to Facilitate Knowledge EngineeringGerhard Wickler

11:50–12:15 Fluent Merging for Classical Planning ProblemsJendrik Seipp, Malte Helmert

11:00–11:25 Finding Mutual Exclusion Invariants in Temporal Planning DomainsSara Bernardini, David E. Smith

Panel Discussion — Proposal(s) for ICKEPS 201214:00–15:30

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KEPS DemosAn Interactive Tool for Plan Visualization, Inspection and GenerationAlfonso E. Gerevini, Alessandro Saetti

VisPlan – Interactive Visualisation and Verification of PlansRadoslav Glinský, Roman Barták

An Extended HTN Knowledge Representation Based on a Graphical NotationFrancisco Palao, Juan Fdez-Olivares, Luis Castillo, Oscar García

KEPS PostersCooperated Integration Framework of Production Planning and Scheduling based on Order Life-cycle ManagementShigeru Fujimura

Relational Approach to Knowledge Engineering for POMDP-based Assistance Systems with Encoding of a Psychological ModelMarek Grzes, Jesse Hoey, Shehroz Khan, Alex Mihailidis, Stephen Czarnuch, Dan Jackson, Andrew Monk

JPDL: A Fresh Approach to Planning Domain ModellingMichael Jonas

Open-Ended Domain Model for Continual Forward Search HTN PlanningDominik Off, Jianwei Zhang

Automatic Polytime Reductions of NP Problems into a Fragment of STRIPSAldo Porco, Alejandro Machado, Blai Bonet

Taking Advantage of Domain Knowledge in Optimal Hierarchical Deepening Search PlanningPascal Schmidt, Florent Teichteil-Königsbuch, Patrick Fabiani

A Conceptual Framework for Post-Design Analysis in AI Planning ApplicationsTiago Stegun Vaquero, José Reinaldo Silva, J. Christopher Beck

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Monte-Carlo Tree Search: Theory and Applications (MCTS)

Welcome

Keynote Speaker

09:15–10:30 Hierarchical Bandits for Sequential Decision MakingRemi Munos

Coffee Break

09:00–09:15

Organizers: Chris Mansley, Alan Fern, Michael Littman, Sergiu GoschinDate and Location: June 12, 2011, Hall 101-00-010/014 Computer Science Campus

11:00–11:30 Repeated-task Canadian Traveler ProblemZahy Bnaya, Ariel Felner, Dror Fried, Solomon Eyal Shimony, Olga Maksin

11:30–12:00 On the Behavior of UCT in Synthetic Search SpacesRaghuram Ramanujan, Ashish Sabharwal, Bart Selman

12:00–12:30 Approaching Bayes-optimality using Monte-Carlo Tree SearchJohn Asmuth, Michael Littman

Lunch Break

14:00–14:30 Guiding Combinatorial Optimization with UCTAshish Sabharwal, Horst Samulowitz

14:30–14:45 Optimistic Planning for Sparsely Stochastic SystemsLucian Busoniu, Remi Munos, Bart De Schutter, Robert Babuska

14:45–15:00 UCT-Treesplit – Parallel MCTS on Distributed MemoryLars Schaefers, Marco Platzner, Ulf Lorenz

Coffee Break

Poster Session15:00–15:30

Poster Session16:00–16:30

Panel Discussion16:30–17:30

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Goal, Activity and Plan Recognition(GAPRec)

Organizers: Christopher Geib, Derek Long, David PattisonDate and Location: June 12, 2011, Hall 101-01-009/013 Computer Science Campus

09:15–09:40 Corpus-Based Incremental Intention Recognition via Bayesian Network Model Construction

Anh Han The, Luís Moniz Pereira

Welcome

09:40–10:05 Towards a System Architecture for Recognizing Domestic Activity by Leveraging a Naturalistic Human Activity Model

Michele Dominici, Myriam Fréjus, Julien Guibourdenche, Bastien Pietropaoli, Frédéric Weis

Coffee Break

09:00–09:15

10:05–10:30 Accurately Determining Intermediate and Terminal Plan States Using Bayesian Goal Recognition

David Pattison, Derek Long

11:00–11:20 Modeling the Human Operator’s Cognitive Process to Enable Assistant System Decisions

Ruben Strenzke

11:20–11:45 Goal Recognition over POMDPs: Inferring the Intention of a POMDP Agent

Miquel Ramírez, Hector Geffner

12:25–12:30 Wrap up

Panel SessionAre we ready for a plan recognition competition and

what can be learnt from the IPC?

11:45–12:25

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Planning and Learning (PAL)

Opening Remarks

Parameter and Portfolio Tuning

09:00–09:20 Instance-Based Parameter Tuning and Learning for Evolutionary AI PlanningMatyas Brendel, Marc Schoenauer

09:20–10:00 FD-Autotune: Domain-Specific Configuration using Fast DownwardChris Fawcett, Malte Helmert, Holger Hoos, Erez Karpas, Gabriele Röger, Jendrik Seipp

+ Generating Fast Domain-Specific Planners by

Automatically Configuring a Generic Parameterised PlannerMauro Vallati, Chris Fawcett, Alfonso E. Gerevini, Holger H. Hoos, Alessandro Saetti

Coffee Break

08:55–09:00

10:00–10:20 Fast Downward Stone Soup: A Baseline for Building Planner PortfoliosMalte Helmert, Gabriele Röger, Erez Karpas

Organizers: Sergio Jiménez Celorrio, Erez Karpas, Subbarao KambhampatiDate and Location: June 13, 2011, Hall 101-00-026 Computer Science Campus

Learning for Domains

11:00–11:25 Learning Domain Control Knowledge for TLPlan and BeyondTomas de la Rosa, Sheila McIlraith

11:25–11:50 Efficient Learning of Action Models for PlanningNeville Mehta, Prasad Tadepalli, Alan Fern

11:50–12:15 Reactive, Proactive, and Passive Learning about Incomplete ActionsChristopher Weber, Daniel Bryce

Lunch Break

Innovations in Learning and Planning

14:00–14:25 Planning in Robocup-Soccer NarrativesHannaneh Hajishirzi, Eyal Amir

14:25–14:50 Cost-Based Learning for PlanningSrinivas Nedunuri, William R. Cook, Douglas R. Smith

14:50–15:15 Learning and Application of High-Level Concepts with Conceptual Spaces and PDDLRichard Cubek, Wolfgang Ertel

12:15–12:30 Discussion

10:20–10:30 Discussion

15:15–15:30 Discussion

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Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS)

Welcome

Scheduling and Resource Allocation

09:05–09:35

A Logic-Based Benders Approach to Scheduling with Alternative Resources and Setup Times

Tony T. Tran, J. Christopher Beck

09:35–10:05

Applying Iterative Flattening Search to the Job Shop Scheduling Problem with Alternative Resources and Sequence Dependent Setup Times

Angelo Oddi, Riccardo Rasconi, Amedeo Cesta, Stephen F. Smith

Coffee Break

09:00–09:05

10:05–10:35

Solving Resource Allocation/Scheduling Problems with Constraint Integer ProgrammingStefan Heinz, J. Christopher Beck

Organizers: Miguel A. Salido, Roman Barták, Nicola Policella Date and Location: June 13, 2011, Hall 101-00-010/014 Computer Science Campus

Planning and SAT

11:00–11:30

Optimization of Partial-Order Plans via MAXSATChristian Muise, Sheila McIlraith, J. Christopher Beck

11:30–12:00

Exploiting MaxSAT for Preference-Based PlanningFarah Juma, Eric Hsu, Sheila McIlraith

12:00–12:30

A SAT Compilation of the Landmark GraphVidal Alcazar, Manuela Veloso

Lunch Break

Modelling and Real-life Problems

14:00–14:30 A Constraint-based Approach for Planning and Scheduling Repeated ActivitiesIrene Barba, Carmelo Del Valle

14:30–15:00 A CFLP Approach for Modeling an Optimization Scheduling ProblemIgnacio Castiñeiras, Fernando Sáenz-Pérez

15:00–15:30 The Distance-Optimal Inter-League Schedule for Japanese Pro BaseballRichard Hoshino, Ken-ichi Kawarabayashi

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Scheduling and Planning Applications woRKshop (SPARK)

Welcome and Introduction

P&S Under Uncertainty & Execution

10:00–10:15 Planning and Replanning for a Constellation of Agile Earth Observation SatellitesRomain Grasset-Bourdel, Gérard Verfaillie, Antoine Flipo

10:15–10:30 Opening the PANDORA-BOX: Planning and Executing Timelines in a Training Environment

Amedeo Cesta, Gabriella Cortellessa, Riccardo De Benedictis, Keith Strickland

Coffee Break

09:00–09:10

Organizers: Gabriella Cortellessa, Minh Do, Riccardo Rasconi, Neil Yorke-SmithDate and Location: June 13, 2011, Hall 101-00-036 Computer Science Campus

P&S Under Uncertainty & Execution cont'd

11:00–11:25 Dynamic Management of Paratransit Vehicle SchedulesZachary Rubinstein, Stephen Smith

11:25–11:50 The Emergency Landing Planner ExperimentNicolas Meuleau, Christian Neukom, Christian Plaunt, David Smith, Tristan Smith

11:50–12:15 Scheduling a Dynamic Aircraft Repair ShopMaliheh Aramon Bajestani, J. Christopher Beck

Lunch Break

12:15–12:30 Commentary and Discussion

Invited Talk

09:10–10:00 Lessons Learned Empowering Smart Applications with Planning TechnologyLuis Castillo Vidal

Invited TalkLuis Castillo VidalLessons Learned Empowering Smart Applications with Planning Technology

Few people would disagree with the success stories of deploying real world planning applications. In this talk we describe the pitfalls we have found since we founded IActive Intelligent Technologies in 2006. IActive specializes in introducing planning technology into existing applications to give them additional decision support capabilities, with tangible and measurable added value. In this talk we discuss the “good” and “not so good” decisions from IActive's experiences.

Schedule

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Coffee Break

Emerging Applications for P&S

16:15–16:30 Temporal Optimization Planning for Fleet RepositioningKevin Tierney, Rune Møller Jensen

16:30–16:45 Knowledge Representations for High-level and Low-level PlanningFranziska Zacharias, Christoph Borst

16:00–16:15 The MMP: A Mixed-Initiative Mission Planning System for the Multi-Aircraft DomainRuben Strenzke, Axel Schulte

16:45–17:05 Command and Control Training Centers: Computer Generated Forces Meet Classical Planning

Carmel Domshlak, Ziv Even-Zur, Yannai Golany, Erez Karpas, Yevgeni Nus

17:05–17:15 Commentary and Discussion

Final Discussion and Closing Remarks17:15–17:45

Novel Domains for P&S

14:00–14:25 Diagnosis As Planning: Two Case StudiesPatrik Haslum, Alban Grastien

14:25–14:40 Computing Genome Edit Distances using Domain-Independent PlanningPatrik Haslum

14:40–15:05 Planning for Human-Robot TeamingKartik Talamadupula, Subbarao Kambhampati, Paul Schermerhorn,

J. Benton, Matthias Scheutz

15:05–15:20 Temporal Planning for Co-Design of Host Scheduling and Workflow Allocation in Mobile Environments

Qiang Lu, Yixin Chen, Mart Haitjema, Catalin Roman, Christopher Gill, Guoliang Chen

15:20–15:30 Commentary and Discussion

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Verification and Validation of Planning and Scheduling Systems (VVPS)

10:00–10:30 Directed Search for Generalized Plans Using Classical PlannersSiddharth Srivastava, Neil Immerman, Shlomo Zilberstein, Tianjiao Zhang

09:00–10:00 Invited Talk: Policy Learning for Autonomous Feature TrackingMaria Fox

Coffee Break

11:00–11:30 Synthesizing and Verifying Plans for Constrained Workflows:Transferring Tools from Formal Methods

Jason Crampton, Michael Huth

Organizers: Saddek Bensalem, Klaus Havelund, Andrea OrlandiniDate and Location: June 13, 2011, Hall 101-01-009/013 Computer Science Campus

11:30–12:00

Predicting Atomicity Violations in Concurrent Programs via PlanningNiloofar Razavi, Azadeh Farzan, Sheila McIlraith

12:00–12:30 A Loop Acceleration Technique to Speed Up Verification of Automatically-Generated Plans

Robert P. Goldman, Michael Pelican, David Musliner

Generating Controllers for Flexible Plan Execution: a TGA ApproachAndrea Orlandini, Alberto Finzi, Amedeo Cesta, Simone Fratini

Lunch Break

14:00–14:30

A Critical Overview and Open Questions for Temporal Planning with UncertaintyRosella Gennari, Anna Roubickova, Marco Roveri

14:30–15:00

Formally Ensuring Time Constraints in a Development ProcessIlias Garnier, Christophe Aussaguès, Vincent David, Guy Vidal-Naquet

15:00–15:30

Coffee Break

Special Session “Darmstadt, we have a problem” –Open Discussion about a Planning Domain

Inspired by an ESA Robotic Mission

16:00–17:30

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TUTORIALS

Sunday, June 12, 2011

A Survey of Suboptimal Search AlgorithmsJordan Thayer, Wheeler Ruml09:00–10:30, Hall 101-02-016/018

Using Solution Length Estimates in Heuristic SearchJordan Thayer, Wheeler Ruml11:00–12:30, Hall 101-02-016/018

Decision Diagrams in Automated Planning and SchedulingScott Sanner14:00–15:30, Hall 101-02-016/018

Problem Solving with Model Checking TechniquesMichael Weber, Jaco van de Pol16:00–17:30, Hall 101-02-016/018

Monday, June 13, 2011

Translation-based Approaches to Conformant and Contingent PlanningHéctor Palacios, Alexandre Albore09:00–10:30, Hall 101-02-016/018

Petri Nets and their Relation to PlanningBlai Bonet, Patrik Haslum11:00–12:30, Hall 101-02-016/018

Open Source Solutions for Motion PlanningSachin Chitta14:00–15:30, Hall 101-01-016/018

Introduction to Planning Domain Modeling in RDDLScott Sanner16:00-17:30, Hall 101-01-016/018

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Decision diagrams have proved to be a useful data structure for model checking, temporal veri-fication, graphical model inference, and factored planning (factored MDPs and POMDPs among many applications). This tutorial will cover the foundations of binary and algebraic decision dia-grams (BDDs & ADDs) – their properties, their al-gorithms, their use in various automated planning settings (including a discussion of when other techniques are preferable to de-cision diagrams), and tricks of the trade (vari-able orderings, approximation, and application-specific operations) that help one

achieve maximal efficiency in practice. Beyond BDDs and ADDs, the tutorial will also cover a variety of less-used but important decision dia-grams and their applications: Zero-suppressed DDs (ZDDs) for set representation, Affine ADDs (AADDs) for arithmetic function representation, recent extensions of decision diagrams to con-tinuous variables, and many others (Factor Edge Value BDDs, Binary Moment Diagrams, etc.) as time permits. While focusing on the theory of de-cision diagrams, the tutorial will constantly re-late the theory to practical applications in automated planning and scheduling.

Decision Diagrams in Automated Planning and SchedulingScott Sanner (NICTA & ANU, Australia) Sunday, June 12, 2011, 14:00–15:30, Hall 101-02-016/018

This tutorial provides a survey of heuristic search algorithms, focusing on algorithms that find suboptimal solutions. We will cover al-gorithms that provide quality bounds, beam search algorithms, and anytime search al-gorithms. The commonality between these famil-

ies of algorithms is that they all sacrifice finding optimal solutions in order to find solutions faster. The goal will be to develop an understanding of when the searches are likely to perform well and when they are likely to perform poorly.

A Survey of Suboptimal Search AlgorithmsJordan Thayer and Wheeler Ruml (University of New Hampshire, USA) Sunday, June 12, 2011, 09:00–10:30, Hall 101-02-016/018

Handling g-value plateaus is an open and challen-ging problem for domain independent planning. One promising approach for dealing with these plateaus is to search on multiple objectives, hop-ing that the guidance of one cost metric will pull the search out of plateaus in another. For cost based planning, plan length is a natural candid-

ate for this additional guidance. This tutorial ex-amines how the field of heuristic search has been tackling the problem of using both solution cost and solution length within a single al-gorithm, with a special focus on how algorithms can incorporate solution length without abandon-ing guarantees on solution quality.

Using Solution Length Estimates in Heuristic SearchJordan Thayer and Wheeler Ruml (University of New Hampshire, USA) Sunday, June 12, 2011, 11:00–12:30, Hall 101-02-016/018

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Abstract:The Model Checking Problem is the question whether a mathematical model (typically of a real-world system) fulfills its specification (often given as a set of logic formulas). Automatic solutions to solve such model checking problems have been researched and refined for close to 30 years now. Since reaching maturity, they have become a standard quality assurance method in, e.g., the semiconductor and aviation industries.In this tutorial, we aim to connect research on model checking and the plethora of techniques it spawned (or incorporated successfully) to strongly related, and sometimes overlapping fields: graph searching, planning, scheduling, artificial intelligence.

Contents:u Introduction to Model Checking: expressing

properties, flavors of models, diagnosticsu Application areas and success stories:

hardware, software, scheduling, puzzle solving, ...

u Conquering the search space: enumerative vs. symbolic methods

u Algorithmic techniques: sequential, directed, multi-core, distributed, and I/O-efficient algorithms (and combinations thereof)

u Symbolic methods: state space compression, binary decision diagrams, translations to SAT problems

u State-of-the-art techniques: CEGAR, bounded model checking, SMT solvers

u Engineering challenges: an explosion of modelling languages and exploration techniques

Problem Solving with Model Checking TechniquesMichael Weber and Jaco van de Pol (University of Twente, Netherlands) Sunday, June 12, 2011, 16:00–17:30, Hall 101-02-016/018

Conformant planning is the problem of finding a sequence of actions for achieving a goal in the presence of uncertainty in the initial state or in action effects. On the other hand, contingent planning is concerned with the problem of achiev-ing goals in the presence of incomplete informa-tion and sensing actions. Both problems have been approached as a path-finding problem in the belief space where good belief representa-tions and heuristics are critical for scaling up. In this tutorial, we present algorithms for both con-formant and contingent planning that rely on translations to classical planning problems, solved by an off-the-shelf classical planner.The first half of this tutorial will be devoted to present translations from conformant planning (i.e., planning with incomplete information and no sensing) into classical planning. Compiled clas-sical problems are solved by a classical planner, taking advantage of heuristics developed for clas-sical planning: as long as heuristics for search-ing in the belief space have not been as successful so far. On top of such a translation was built the T0 conformant planner, best per-former of the conformant track at IPC 2006. These general translation schemes are sound

and we establish the conditions under which such translations are also complete. Thus, we present the notion of conformant width, that characterizes the size of classical translations that are guaranteed to be complete.In the second half of the tutorial, we will focus on how to build efficient action selection mechan-isms for planning with sensing (contingent plan-ning) on top of conformant planning translations. In fact, the ability to find conformant plans is needed in contingent settings where conformant situations constitute a special case. Planning with incomplete information and partial observ-ability is the most complex setting for planning. We will show how to obtain a closed-loop al-gorithm for achieving the goal in planning with sensing, using a conformant translation. Also, we will introduce the notion of contingent width, sim-ilar to the former conformant width, to character-ize contingent planning problems.Finally, building on the same translations, we will show how to obtain robust finite-state control-lers. Finite-state and memoryless controllers are simple action selection mechanisms widely used in domains such as video games and mobile ro-botics. We show how to develop a model-based

Translation-based Approaches to Conformant and Contingent PlanningHéctor Palacios (Universidad Carlos III de Madrid, Spain) and Alexandre Albore (Universitat Pompeu Fabra, Spain) Monday, June 13, 2011, 09:00–10:30, Hall 101-02-016/018

20

Petri nets are a formalism for modelling discrete dynamical systems, widely used in automated verification (model checking). There is a wealth of results and algorithmic techniques for Petri nets, often based on principles quite different from those commonly employed in planning.

This tutorial aims to present the basics of Petri nets, with focus on their relation to modelling formalisms used in planning and the exchange of algorithmic techniques between the two fields.

Petri Nets and their Relation to PlanningBlai Bonet (Universidad Simón Bolívar, Venezuela) and Patrik Haslum (NICTA & ANU, Australia) Monday, June 13, 2011, 11:00–12:30, Hall 101-02-016/018

This tutorial will focus on the application of motion planning for mobile manipulation in unstructured environments. Topics will include the following:u integrating real time sensing with planning to deal with dynamic environmentsu integrating planning and reactive control for mobile manipulationu dealing with kinematic constraintsu plan monitoring and replanning in dynamic environmentsu combining different planning techniquesu application of these techniques to real world problems in object manipulation, door opening, cart

pushing

Open Source Solutions for Motion PlanningSachin Chitta (Willow Garage) Monday, June 13, 2011, 14:00–15:30, Hall 101-01-016/018

method for deriving finite-state controllers auto-matically. In particular, the models represent a class of contingent problems where actions are deterministic and some fluents are observable. The problem of deriving a controller from such models is converted into a conformant planning problem that is solved using classical planners, taking advantage of a complete translation intro-duced before. All algorithms will be illustrated with examples.

We expect the tutorial to be interesting for gener-al AI researchers, as we build on simple ideas that have been successful and that we introduce step by step. We will discuss other similar ap-proaches and their limits, e.g., how a representa-tion affects heuristic search, to put the translations introduced into context.

RDDL is the Relational Dynamic Influence Dia-gram Language, the domain modeling language used in the ICAPS 2011 International Probabilist-ic Planning Competition. RDDL has been de-veloped to compactly model real-world planning problems that use boolean, multi-valued, integer and continuous variables, unrestricted concur-rency, non-fluents, probabilistic independence among complex effects (important for exogen-ous events), aggregation operators in addition to quantifiers, and partial observability. While RDDL addresses some of the probabilistic modeling lim-

itations of PPDDL, its deterministic subset also addresses some modeling limitations of PDDL (e.g., models needing nonlinear difference equa-tions or unrestricted concurrency). This tutorial provides a general introduction to RDDL, its se-mantics, and a number of detailed examples like elevator and traffic control to demonstrate its ex-pressive power. It also provides a brief introduc-tion to the rddlsim software that permits the simulation, evaluation, and visualization of plan-ners and planning domains.

Introduction to Planning Domain Modeling in RDDLScott Sanner (NICTA & ANU, Australia) Monday, June 13, 2011, 16:00–17:30, Hall 101-01-016/018

21

MAIN CONFERENCE PROGRAM

The main program will be hosted at

Kollegiengebäude I (KG I)Platz der Universität 379098 Freiburg

Map data © OpenStreetMap contributors, CC-BY-SA; based on a map by Frederik Ramm and Jochen Topf

22

Tuesday, June 14, 2011, AM08

:45–

09:0

0O

peni

ng R

emar

ksHa

ll: A

ula

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euri

stic

s fo

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anni

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ll: H

S 11

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air:

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Kam

bham

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Whe

re Ig

norin

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elet

e Li

sts

Wor

ks,

Part

II: C

ausa

l Gra

phs

Jörg

Hof

fman

n

09:0

0–10

:00

Invi

ted

Talk

: Spo

ken

Dia

log

Syst

ems

as a

n Ap

plic

atio

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Pla

nnin

g un

der

Unc

erta

inty

Jaso

n D.

Will

iam

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ula

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Chai

r: St

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10:0

0–10

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10:3

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arko

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Proc

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ula

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Chai

r: Sy

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Thi

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Heu

ristic

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for

Gen

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chas

tic

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test

Pat

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DPs

Andr

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anie

l S. W

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Héc

tor G

effn

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Whe

n O

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: Le

arni

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ast

Info

rmat

ive

Actio

n Co

st P

artit

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ngs

Erez

Kar

pas,

Mic

hael

Kat

z, S

haul

Mar

kovi

tch

Effic

ient

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icy

Cons

truc

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for

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epre

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Pr

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uno

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ttini

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anni

ng w

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AT a

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Solu

tions

Pasc

al P

oupa

rt, K

ee-E

ung

Kim

, Don

gho

Kim

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G-P

: Rel

axed

Pla

n H

euris

tics

for

Plan

ning

with

Pre

fere

nces

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da C

oles

, And

rew

Col

es

Mar

kov

Dec

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n Pr

oces

ses

with

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inal

Rew

ards

: Re

fere

nce

Poin

t-Ba

sed

Pref

eren

ces

Paul

Wen

g

12:1

0–14

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h Br

eak

(ind

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ual,

no o

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ized

lunc

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ed)

Dyn

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pace

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in

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ory

Gra

ph S

earc

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hou,

Eric

A. H

anse

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ener

aliz

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lann

ing

Hall:

Aul

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air:

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lann

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A

Best

-Res

pons

e Ap

proa

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ders

Jons

son,

Mic

hael

Rov

atso

s

23

IIa: P

lan

Sear

ch E

ngin

eeri

ngHa

ll: H

S 11

99Se

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air:

Patr

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in

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Gra

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earc

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hou,

Eric

A. H

anse

n

14:0

0–15

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IIb: G

ener

aliz

ed P

lann

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Hall:

Aul

aSe

ssio

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cIlra

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Scal

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Up

Mul

tiage

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lann

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pons

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chAn

ders

Jons

son,

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of t

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Loos

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trib

uted

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trol

of S

ituat

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tanc

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rge

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ains

with

Man

y Ta

sks

Jess

e Ho

ey, M

arek

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Dire

cted

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rch

for

Gen

eral

ized

Pla

ns

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lass

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nner

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ddha

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erm

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ristic

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ions

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et(s

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talk

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ffect

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to

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anni

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erev

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essa

ndro

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tti(s

hort

talk

)

15:3

5–16

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Resu

lts

IPC

Hall:

HS

1199

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ion

Chai

r: Án

gel G

arcí

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Det

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inis

tic C

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arcí

a Ol

aya,

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los

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res

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z, S

ergi

o Jim

énez

Cel

orrio

16:0

5–16

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erta

inty

Com

petit

ion

Scot

t San

ner,

Sung

woo

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mén

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man

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17:3

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(ope

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d)D

octo

ral C

onso

rtiu

m P

oste

rs &

Sys

tem

Dem

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ll: A

ula

and

Prom

ethe

us

Tuesday, June 14, 2011, PM

Ligh

t app

etiz

ers

and

drin

ks w

ill b

e se

rved

dur

ing

the

post

ers

and

syst

em d

emos

ses

sion

.

17:1

0–17

:30

16:3

0–17

:10

24

09:0

0–10

:00

Invi

ted

Talk

: Las

t-M

ile D

isas

ter

Prep

ared

ness

and

Rec

over

yPa

scal

Van

Hen

tenr

yck

Hall:

Aul

aSe

ssio

n Ch

air:

Fahi

em B

acch

us

10:0

0–10

:30

Coff

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reak

IIIa:

App

licat

ions

IRo

om: H

S 11

99Se

ssio

n Ch

air:

Scot

t San

ner

Cost

-Sen

sitiv

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ncur

rent

Pla

nnin

g un

der

Dur

atio

n U

ncer

tain

ty fo

r Se

rvic

e-Le

vel A

gree

men

tsAm

anda

Col

es, A

ndre

w C

oles

, Alla

n Cl

ark,

Ste

phen

Gilm

ore

10:3

0–12

:10

IIIb:

Fro

ntie

rs in

Pla

nnin

gHa

ll: A

ula

Sess

ion

Chai

r: Da

vid

Smith

Lear

ning

Inad

mis

sibl

e H

euris

tics

durin

g Se

arch

Jord

an T

. Tha

yer,

Aust

in D

ionn

e, W

heel

er R

uml

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Plan

ning

for

a M

ater

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ontr

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m fo

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quid

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Dis

play

Man

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turin

gM

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Do, K

azum

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Oka

jima,

Ser

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ckun

, Fu

mio

Has

egaw

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ukih

iro K

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oji T

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ing

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g, A

ki O

hash

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Ense

mbl

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onte

-Car

lo P

lann

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An

Em

piric

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tudy

Alan

Fer

n, P

aul L

ewis

Plan

ning

Mul

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nspo

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lem

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sé E

. Fló

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aro

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alba

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na, J

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cía,

Ca

rlos

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Gar

cía

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a, D

anie

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Effe

ctiv

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euris

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and

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f Tra

ckin

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r Pl

anni

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ith In

com

plet

e In

form

atio

nAl

exan

dre

Albo

re, M

ique

l Ram

írez,

Héc

tor G

effn

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th P

lann

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Algo

rithm

for

an A

UV

Gui

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with

Hom

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asse

sEm

ili H

erna

ndez

, Mar

c Ca

rrera

s, P

ere

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o

Sear

chin

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r Pl

ans

with

Car

eful

ly D

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Prob

esNi

r Lip

ovet

zky,

Héc

tor G

effn

er

12:1

0–14

:00

Lunc

h Br

eak

(ind

ivid

ual,

no o

rgan

ized

lunc

h pr

ovid

ed)

Wednesday, June 15, 2011, AM

Auto

mat

ic C

onst

ruct

ion

of E

ffici

ent

Mul

tiple

Bat

tery

Usa

ge P

olic

ies

Mar

ia F

ox, D

erek

Lon

g, D

anie

le M

agaz

zeni

(bes

t pa

per)

25

IV: B

est

Pape

rsHa

ll: A

ula

Sess

ion

Chai

r: M

alte

Hel

mer

t

Auto

mat

ic C

onst

ruct

ion

of E

ffici

ent

Mul

tiple

Bat

tery

Usa

ge P

olic

ies

Mar

ia F

ox, D

erek

Lon

g, D

anie

le M

agaz

zeni

(bes

t pa

per)

14:0

0–15

:40

Com

putin

g Al

l-Pai

rs S

hort

est

Path

s by

Lev

erag

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Tre

ewid

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lank

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js d

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gt(h

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men

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for

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Sam

plin

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lann

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Ragh

uram

Ram

anuj

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art S

elm

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tion

for

best

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pap

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Plan

ning

to

Perc

eive

: Exp

loiti

ng M

obili

ty F

or R

obus

t O

bjec

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etec

tion

Javi

er V

elez

, Gar

rett

Hem

ann,

Alb

ert S

. Hua

ng, I

ngm

ar P

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r, Ni

chol

as R

oy(b

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stud

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pape

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15:4

0–16

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Coff

ee B

reak

16:1

0–18

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Com

mun

ity

Mee

ting

(inc

lude

s Be

st D

isse

rtat

ion

Talk

and

Aw

ards

Cer

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ll: A

ula

Sess

ion

Chai

r: Sh

lom

o Zi

lber

stei

n

20:0

0Ba

nque

t

Wednesday, June 15, 2011, PM

26

09:0

0–10

:00

Invi

ted

Talk

: Em

piric

al G

ame-

Theo

retic

Ana

lysi

s an

d th

e Be

havi

or o

f Sof

twar

e Ag

ents

Mic

hael

P. W

ellm

anHa

ll: A

ula

Sess

ion

Chai

r: Ca

rmel

Dom

shla

k

10:0

0–10

:30

Coff

ee B

reak

Va: A

pplic

atio

ns II

Hall:

HS

1199

Sess

ion

Chai

r: M

aria

Fox

Cros

s-D

omai

n Ac

tion-

Mod

el A

cqui

sitio

n fo

r Pl

anni

ng V

ia W

eb S

earc

hHa

nkz

Hank

ui Z

huo,

Qia

ng Y

ang,

Ron

g Pa

n, L

ei L

i

10:3

0–12

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Vb: L

imit

s an

d Po

ssib

iliti

esHa

ll: A

ula

Sess

ion

Chai

r: Jö

rg H

offm

ann

Lim

its fo

r Co

mpa

ct R

epre

sent

atio

ns o

f Pla

nsCh

riste

r Bäc

kströ

m, P

eter

Jons

son

Pote

ntia

l Sea

rch:

A B

ound

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Sear

ch A

lgor

ithm

Roni

Ste

rn, R

ami P

uzis

, Arie

l Fel

ner

Auto

mat

ic P

olyt

ime

Redu

ctio

ns o

f NP

Prob

lem

s in

to a

Fr

agm

ent

of S

TRIP

SAl

do P

orco

, Ale

jand

ro M

acha

do, B

lai B

onet

Visu

al P

rogr

amm

ing

of P

lan

Dyn

amic

s U

sing

Con

stra

ints

and

Lan

dmar

ksJu

lie P

orte

ous,

Jona

than

Teut

enbe

rg,

Davi

d Pi

zzi,

Mar

c Ca

vazz

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A Co

mpl

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Algo

rithm

for

Gen

erat

ing

Land

mar

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ai B

onet

, Jul

io C

astil

lo(s

hort

talk

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urna

men

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oble

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char

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Out

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min

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ion

for

Prob

abili

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Pla

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omas

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ler,

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Sam

ple-

Base

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anni

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ntin

uous

Act

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Mar

kov

Dec

isio

n Pr

oces

ses

Chris

Man

sley

, Ari

Wei

nste

in, M

icha

el L

. Litt

man

(sho

rt ta

lk)

12:1

5–14

:00

Lunc

h Br

eak

(ind

ivid

ual,

no o

rgan

ized

lunc

h pr

ovid

ed)

Thursday, June 16, 2011, AM

Sche

dulin

g an

Airc

raft

Rep

air

Shop

Mal

iheh

Ara

mon

Baj

esta

ni, J

. Chr

isto

pher

Bec

k

VIb:

Inco

mpl

ete

Info

rmat

ion

Hall:

Aul

aSe

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n Ch

air:

Pasc

al P

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Plan

ning

and

Act

ing

in In

com

plet

e D

omai

nsCh

risto

pher

Web

er, D

anie

l Bry

ce

27

VIa:

Aut

omat

ed S

ched

ulin

gHa

ll: H

S 11

99Se

ssio

n Ch

air:

Dani

el B

orra

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dulin

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Shop

Mal

iheh

Ara

mon

Baj

esta

ni, J

. Chr

isto

pher

Bec

k

14:0

0–15

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VIb:

Inco

mpl

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Info

rmat

ion

Hall:

Aul

aSe

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n Ch

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Pasc

al P

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in In

com

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Web

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Scal

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VIIa

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15:4

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VIIb

: App

licat

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III

Hall:

Aul

aSe

ssio

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air:

Gabr

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Rög

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The

Min

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Plan

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Pro

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16:2

5–16

:30

Clos

ing

Rem

arks

Hall:

Aul

a

Thursday, June 16, 2011, PM

28

FlowOpt: A Set of Tools for Modeling, Optimizing, Analyzing, and Visualizing Production WorkflowsRoman Barták, Martin Cully, Milan Jaška, Ladislav Novák, Vladimír Rovenský, Con Sheahan, Tomáš Skalický, Dang Thanh-Tung

Only Hope remains in the PANDORA’s .jar – Pervasive Use of Planning in a Training EnvironmentGiulio Bernardi, Amedeo Cesta, Luca Coraci, Gabriella Cortellessa, Riccardo De Benedictis, Francois Mohier, Jure Polutnik, Miha Vuk

Command and Control Training Centers: Computer Generated Forces Meet Classical PlanningCarmel Domshlak, Ziv Even-Zur, Yannai Golany, Erez Karpas

Constraint Priorities – a Way to Get an Optimal Timetable Fully Automatically.Three Steps into the Modern Timetable Scheduler - www.school-timetable.euWiesław Dudek

Planning Multi-modal Transportation ProblemsJose E. Florez, Alvaro Torralba, Javier García, Carlos Linares López, Ángel García Olaya, Daniel Borrajo

PLANET: a Planning and Replanning Tool for a Constellation of Agile Earth-observing SatellitesRomain Grasset-Bourdel, Gérard Verfaillie, Antoine Flipo

Building a Domain-Independent Architecture for Planning, Learning and Execution (PELEA)Cesar Guzman, Vidal Alcázar, David Prior, Eva Onaindía, Daniel Borrajo, Juan Fdez-Olivares

Dora, a Robot Exploiting Probabilistic Knowledge under Uncertain Sensing for Efficient Object SearchMarc Hanheide, Charles Gretton, Moritz Göbelbecker

A Path Planning Algorithm for an AUV Guided with Homotopy ClassesEmili Hernandez, Marc Carreras, Pere Ridao

The TorchLight Tool: Analyzing Search Topology Without Running Any SearchJörg Hoffmann

The “DUKC Optimiser” Ship Scheduling SystemElena Kelareva

WindMT: An Integrated System for Failure Detection and Maintenance Scheduling at Wind FarmsAndras Kovacs, Janos Csempesz, Gabor Erdos, David Karnok, Lorinc Kemeny, Laszlo Monostori, Zsolt Janos Viharos

Demonstration of the Emergency Landing PlannerElif Kurklu, Nicolas Meuleau, Christian Neukom, Christian Plaunt, David E. Smith, Tristan Smith

Organizers: Piergiorgio Bertoli, Minh DoDate and Location: June 14, 2011, Prometheus Hall and Aula

The winner of the Best System Demo Award will be determined by a ballot.

SYSTEM DEMONSTRATIONS

29

Scheduling and Planning Interface for Exploration (SPIFe)Mike McCurdy, Arash Aghevli, Alfredo Bencomo

A New Approach to Conformant Planning via Classical PlannersKhoi Nguyen, Vien Tran, Tran Cao Son, Enrico Pontelli

Automatic Polytime Reductions of NP Problems into a Fragment of STRIPSAldo Porco, Alejandro Machado, Blai Bonet

A Visual Programming Interface for Specifying Plan DynamicsJulie Porteous, Jonathan Teutenberg, David Pizzi, Fred Charles, Marc Cavazza

Beyond Calendar Mashups: SELFPLANNER 2.0Ioannis Refanidis, Anastasios Alexiadis, Neil Yorke-Smith

Planning for Agents with Changing GoalsKartik Talamadupula, Paul Schermerhorn, J. Benton, Subbarao Kambhampati, Matthias Scheutz

Scheduling Print Jobs in Lean Document Production (LDP) ToolkitRong Zhou, Sudhendu Rai, Minh Do

DOCTORAL CONSORTIUM POSTERS

Malileh Aramon Bajestani Combining Stochastic Models of Maintenance with Optimization-based Scheduling Decisions

J. BentonPartial Satisfaction Planning: Representations and Solving Methods

Will CushingTemporal Planning

Masood Feyzbakhsh-RankoohUsing a Complete Heuristic Search for State-Space Based Temporal Planning

Avitan GefenModeling Planning Problems using Hypergraphs

Bharat Ranjan KavuluriThe Invariant Class of Problems

Elena KelarevaShip Scheduling with Uncertainty

Andrey KolobovHeuristic Search for Generalized Stochastic Shortest Path MDPs

Fabien LagriffoulA Framework for Hybrid Planning

Alejandro Machado Translating Decision Problems into Planning Tasks

Organizers: Patrik Haslum, Héctor Geffner, Subbarao KambhampatiDate and Location: June 14, 2011, Prometheus Hall and Aula

30

Aldo PorcoAutomatic Polytime Reductions of NP Problems into a Fragment of STRIPS

Maria Viviane de MenezesModel Update for Automated Planning

Gonzalo Milla MillanLearning HTN Planning Domains from Plan Traces

Daniel MorwoodGoal-Directed Knowledge Acquisition

Srinivas NedunuriDominance Relations for Better Plans and Planners

Khoi NguyenConformant Planning via Classical Planners

Léon PlankenSolving and Coordinating the Simple Temporal Problem

Nir PochterPruning Techniques in Search and Planning

Ezequiel QuinteroImproving Plan Execution on Mobile Robots by Learning Action Durations

Inmaculada Sánchez GarzónA Repair-Replanning Strategy for HTN Planning Frameworks

Joris ScharpffDynamic Contracting and Road Blocks

Ruben StrenzkeHuman-Machine Mixed-Initiative Cooperation in Multi-UAV Mission Planning

Kartik TalamadupulaPlanning for Human-Robot Teaming in Open Worlds

Kevin TierneyFleet Repositioning with Temporal Optimization Planning

Son ToOn the Effectiveness of Belief State Representation in Planning under Uncertainty

Mauro VallatiConfiguration and Learning Techniques for Efficient Automated Planning Systems

31

SOCIAL PROGRAM

Map data © OpenStreetMap contributors, CC-BY-SA; based on a map by Frederik Ramm and Jochen Topf

Opening Reception

Banquet

© FWTMHistorisches Kaufhaus

Mon, June 13, 19:30–22:00

Historisches KaufhausMünsterplatz 2479098 Freiburg

Wed, June 15, 20:00

Schlossbergrestaurant DattlerAm Schloßberg 179104 Freiburg im Breisgau

32

Invi

ted

Talk

: Mic

hael

P. W

ellm

anHa

ll: A

ula Vb

: Lim

its

and

Poss

ibili

ties

Hall:

Aul

a

VIb:

In

com

plet

e In

form

atio

nHa

ll: A

ula

VIIb

: Ap

plic

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ns

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Internet AccessWireless internet access is available near the conference halls.

Participants from eduroam institutions can use their usual authentication process to connect toWLANuni-fr (available all over the campus).

Other participants can use the following authentication:Network: ICAPSPassword: omitted in online version

GENERAL INFORMATION

Registration DeskJune 11–13:The registration desk is located in the foyer of building 101 on the computer science campus.Saturday, June 11: 10:00–15:00Sunday and Monday, June 12 and 13: 8:00–18:00

June 14–16:The registration desk is located in the Prometheus hall in front of the Aula in building KG I.Tuesday, June 14: 8:00–20:00Wednesday, June 15: 8:30–18:00Thursday, June 16: 8:30–16:45

OrganizationICAPS 2011 has been organized by the University of Freiburg in cooperation withkongress & kommunikation gGmbH.

We wish to thank the following for their contribution to the success of this conference:

European Office of Aerospace Research and Development,Air Force Office of Scientific Research, United StatesAir Force Research Laboratory (http://www.london.af.mil).

LunchesLunches are included for all conference participants on Sunday and Monday (served in the foyer of building 101 on the computer science campus). For DC participants and mentors, lunch is also included on Saturday (same location). On all other days, lunch is individual (no organized lunch provided) with plenty of options near the conference venue.

ICAPS 2011 SATELLITE EVENTS AT A GLANCE

Coffee Break

HDIP101-00-026

AM 1 KEPS101-00-036

Sunday, June 12

MCTS101-00-010/014

GAPRec101-01-009/013

Tutorial 1101-02-016/018

HDIP101-00-026

AM 2 KEPS101-00-036

MCTS101-00-010/014

GAPRec101-01-009/013

Tutorial 2101-02-016/018

Lunch Break

HDIP101-00-026

PM 1 KEPS101-00-036

MCTS101-00-010/014

Tutorial 3101-02-016/018

HDIP101-00-026

PM 2 KEPS101-00-036

MCTS101-00-010/014

Tutorial 4101-02-016/018

Coffee Break

Coffee Break

PAL101-00-026

AM 1 SPARK101-00-036

COPLAS101-00-010/014

VVPS101-01-009/013

Tutorial 5101-02-016/018

PAL101-00-026

AM 2 SPARK101-00-036

COPLAS101-00-010/014

VVPS101-01-009/013

Tutorial 6101-02-016/018

Lunch Break

PAL101-00-026

PM 1 SPARK101-00-036

COPLAS101-00-010/014

Tutorial 7101-01-016/018

PM 2 SPARK101-00-036

Coffee Break

VVPS101-01-009/013

VVPS101-01-009/013

Monday, June 13

Tutorial 1: A Survey of Suboptimal Search Algorithms (Jordan Thayer and Wheeler Ruml)Tutorial 2: Using Solution Length Estimates in Heuristic Search (Jordan Thayer and Wheeler Ruml)Tutorial 3: Decision Diagrams in Automated Planning and Scheduling (Scott Sanner)Tutorial 4: Problem Solving with Model Checking Techniques (Michael Weber and Jaco van de Pol)

Tutorial 5: Translation-based Approaches to Conformant and Contingent Planning(Héctor Palacios and Alexandre Albore)

Tutorial 6: Petri Nets and their Relation to Planning (Blai Bonet and Patrik Haslum)Tutorial 7: Open Source Solutions for Motion Planning (Sachin Chitta)Tutorial 8: Introduction to Planning Domain Modeling in RDDL (Scott Sanner)

Saturday, June 11Doctoral Consortium

Tutorial 8101-01-016/018

IIa: P

lan

Sear

ch

Engi

neer

ing

Hall:

HS

1199

14:0

0–15

:35

IIb:

Gen

eral

ized

Pl

anni

ngHa

ll: A

ula

15:3

5–16

:05

Coff

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Resu

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Hall:

HS

1199

16:0

5–17

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17:3

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Dem

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08:4

5–09

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Ope

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Rem

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Hall:

Aul

a

Ia: H

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anni

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S 11

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09:0

0–10

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Invi

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Talk

: Jas

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10:0

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10:3

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12:1

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Invi

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Talk

: Pas

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Hent

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10:0

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IIIa:

Ap

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HS

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10:3

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14:0

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15:4

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and

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Hall:

Aul

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20:0

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09:0

0–10

:00

Invi

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Talk

: Mic

hael

P. W

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ula

10:0

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Va:

Appl

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II

Hall:

HS

1199

10:3

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imit

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ula

12:1

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tom

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Sc

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Hall:

HS

1199

14:0

0–15

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VIb:

In

com

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form

atio

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ll: A

ula

15:1

5–15

:45

Coff

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VIIa

: Rea

l-Ti

me

Plan

ning

Hall:

HS

1199

15:4

5–16

:25

VIIb

: Ap

plic

atio

ns

IIIHa

ll: A

ula

16:2

5–16

:30

Clos

ing

Rem

arks

Hall:

Aul

a

ICAP

S 20

11 M

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ON

FERE

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14

Wed

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9:30–2

2:00

, at t

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(nex

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).