ICAPS'08 Workshop Program
ICAPS-WS1: Constraint Satisfaction Techniques for Planning and Scheduling
Miguel A. Salido, Antonio Garrido, Roman Barták, Amedeo Cestaweb site
The areas of AI planning and scheduling have seen important advances thanks to the application of constraint satisfaction models and techniques. Now, solutions to many real-world problems that comprise a mixture of planning and scheduling need to integrate plan synthesis capabilities with resource allocation, which can be efficiently managed by using constraint techniques.
The workshop will aim at providing a forum to discuss novel issues on planning, scheduling, constraint satisfaction problems (CSPs) and common interrelated areas. More specifically, the workshop topics include: 1) planning (temporal planning, multi-criteria planning, planning with resources, etc.), 2) scheduling (constraint management, temporal networks, etc.), 3) integration of planning and scheduling (from a CSP perspective), 4) temporal CSPs, 5) heuristic techniques for multiple objectives, and 6) distributed/multi-agent planning and scheduling. These topics make this workshop very appealing for the potential attendees of the ICAPS conference, particularly these years when ICAPS is collocated with CP, which is the annual international conference on constraint programming and also especially encourages workshops related to planning and scheduling. This common interest will provide a broader audience to the workshop and give the participants the opportunity to exchange ideas and approaches that lead to a valuable and fruitful discussion, and inspire forthcoming research.
ICAPS-WS2: Knowledge Engineering for Planning and Scheduling
Roman Barták, Lee McCluskeyweb site
Despite the progress in automated planning and scheduling systems, these systems still need to be fed by problem description and they need to be fine tuned for particular domains or problems. Knowledge engineering for AI planning and scheduling deals with the acquisition, validation and maintenance of domain models, and the selection and optimization of appropriate machinery to work on them. The importance of knowledge engineering techniques is clearly demonstrated by a performance gap between domain-independent planners and planners exploiting domain dependent knowledge.
ICAPS-WS3: Scheduling and Planning Applications
Luis Castillo, Gabriella Cortellessa, Neil Yorke-Smithweb site
The aim of this workshop is to provide a stable, long-term forum collocated with ICAPS (International Conference on Automated Planning and Scheduling) where researchers can discuss about the applications of planning and scheduling techniques to real problems in contrast to academic toy benchmarks. That is, these domains and instances should be under study for, or closely inspired by, a real industrial/commercial deployment of P&S techniques. This workshop follows antecedent meetings at previous years of ICAPS, particularly the ICAPS'07 Workshop on Moving Planning and Scheduling Systems into the Real World. Challenges and discussions from one year's edition will be used to set the baseline for the successive editions so that the workshop fosters an evolving and cumulative perspective of the applications and their challenges along the years. This effort is intended to converge to a medium/large term set of challenges that could be of benefit for the research community. Authors of accepted papers will be encouraged to share their domains and instances or part of them to start up a library of practical benchmarking problems that could also be useful for the community.
ICAPS-WS4: Multiagent Planning
Matthijs Spaan, Mathijs de Weerdt, Brad Clement, Shlomo Zilbersteinweb site
Planning for multiagent systems is a broad field with many applications, but its subfields remain rather dispersed. This workshop aims to bring together researchers working on multiagent planning to bridge the gap between several communities. Approaches to multiagent planning can characterized along several axes, for instance whether individual agents are considered to be cooperative or self-interested. A second matter is how uncertainty in models of the environment is represented and tackled. Furthermore, some approaches consider computing a multiagent plan off-line, while others focus on coordinating individual plans. Despite this diversity many shared problem exist, and this workshop allows for discussion of common issues and challenges.
Potential topics include:
- distributed plan management
- coordination of single-agent planners
- multiagent planning under uncertainty
- game theoretic planning (cooperative and competitive)
- communication issues in distributed planning
- applications of multiagent planning
ICAPS-WS5: A Reality Check for Planning and Scheduling Under Uncertainty
Daniel Bryce, Mausam, Sungwook Yoonweb site
Research on planning and scheduling under uncertainty is one of most active areas in AI today. Many applications motivate the need to cope with uncertainty due to effectors, sensors, environment, adversaries, allies, and even the imperfect planning agent. However, the benefit of techniques falling within this category is highly contentious for many (provocative) reasons:
- The scalability of probabilistic/decision theoretic planners is a far cry from that of deterministic planners.
- Re-planners dominate conditional (pre)planners in the IPC.
- Several domains involving uncertainty are not probabilistically interesting, and hence, deterministic planners suffice for such domains.
- Acquiring models (e.g., probability distributions) from humans is difficult and often times subjective, whereas learning models can sometimes be more successful with hard-to-come-by, but good data.
- Much work concentrates on optimal (or approximately optimal) solutions, despite the limited success of such techniques in even deterministic settings.
- Models of the uncertainty in real-world scheduling domains are often so poor, or the variability between instances so great, that complex anticipatory scheduling approaches render schedules brittle and suboptimal with hindsight.
- The research community has studied abstracted benchmarks and produced dedicated algorithms that fail to impact real-world scheduling instances. Practitioners favor straightforward deterministic scheduling techniques combined with online schedule refinement and repair.
Topics include, but are not limited to:
- Responses to the provocations above: for or against.
- Models and languages for planning and scheduling under uncertainty.
- Knowledge acquisition for models of uncertainty.
- Replanning versus Conditional (Pre)Planning.
- Algorithm selection based on domain analysis.
- Scaling planning and scheduling under uncertainty.
- Applications of planning and scheduling under uncertainty.
- Execution and execution monitoring in uncertain environments.
- Adversarial or multi-agent techniques.
ICAPS-WS6: Oversubscribed Planning & Scheduling
Laura Barbulescu, Steve Chien, Mark Giuliano, Rob Sherwoodweb site
In many planning and scheduling applications it is not possible to achieve all requested goals. For example, in space mission scheduling it may not be possible to observe all of the requested targets. Similarly, in manufacturing it may not be possible to fulfill all of the production orders. This workshop targets problems and techniques for planning and scheduling problems where it is not possible to achieve all of the problem goals. As such, it often includes representation of optimization, preferences, and/or cost to provide guidance as to desirability over partial solutions. The topics of discussion at this workshop include:
- algorithms for oversubscribed planning and scheduling
- hybrid techniques for oversubscribed planning and scheduling
- application areas involving oversubscribed planning and scheduling
- comparison of planning and scheduling approaches to oversubscribed problems in both deployed applications and testbed problem sets
- evaluation of techniques for oversubscribed planning & scheduling
- operations research based approaches
- methods of representing preferences, objective functions, etc.
- Ronen Brafman, Ben-Gurion University, brafman AT cs.bgu.ac.il