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This book constitutes the thoroughly refereed post-proceedings of the 5th European Conference on Planning, ECP'99, held in Durham, UK, in September 1999.
The 27 revised full papers presented together with one invited survey were carefully reviewed and selected for inclusion in the book. They address all current aspects of AI planning and scheduling. Several prominent planning paradigms are represented, including planning as satisfiability and other model checking strategies, planning as heuristic state-space search, and Graph-plan-based approaches. Moreover, various new scheduling approaches and combinations of planning and scheduling methods are introduced.
Planning as Model Checking.- Conformant Planning via Model Checking.- Strong Cyclic Planning Revisited.- Scaleability in Planning.- Exploiting Competitive Planner Performance.- A Parallel Algorithm for POMDP Solution.- Plan Merging & Plan Reuse as Satisfiability.- SAT-Based Procedures for Temporal Reasoning.- Numeric State Variables in Constraint-Based Planning.- Hierarchical Task Network Planning as Satisfiability.- Exhibiting Knowledge in Planning Problems to Minimize State Encoding Length.- Action Constraints for Planning.- Least Commitment on Variable Binding in Presence of Incomplete Knowledge.- Scaling up Planning by Teasing Out Resource Scheduling.- Real-Time Scheduling for Multi-agent Call Center Automation.- Task Decomposition Support to Reactive Scheduling.- Greedy Algorithms for the Multi-capacitated Metric Scheduling Problem.- Automata-Theoretic Approach to Planning for Temporally Extended Goals.- Integer Programs and Valid Inequalities for Planning Problems.- Deductive Synthesis of Recursive Plans in Linear Logic.- Sensor Planning with Non-linear Utility Functions.- Propice-Plan: Toward a Unified Framework for Planning and Execution.- What is the Expressive Power of Disjunctive Preconditions?.- Some Results on the Complexity of Planning with Incomplete Information.- Probabilistic Planning in the Graphplan Framework.- Making Graphplan Goal-Directed.- GRT: A Domain Independent Heuristic for STRIPS Worlds Based on Greedy Regression Tables.- Planning as Heuristic Search: New Results.