Applicants are expected to be conducting research in the field of Automated Planning & Scheduling; topics of interest include (but are not limited to):

Algorithms: novel planning and scheduling algorithms.

Applications: Empirical studies of existing planning/scheduling systems; domain-specific techniques; heuristic techniques; user interfaces for planning and scheduling; evaluation metrics for plans/schedules; verification and validation of plans/schedules. Application examples of real world problems are particularly welcomed.

Architectures: Real-time support for planning/scheduling/control; mixed-initiative planning and user interfaces; integration of planning and scheduling; continuous planning systems; integration of planning/scheduling and Fault Detection Isolation and Recovery (FDIR); planning and scheduling in autonomous systems.

Environmental and Task Models: Analyses of the dynamics of environments, tasks, and domains with regard to different models of planning and execution; verification and validation of domain models.

Formal Models: Reasoning about knowledge, action, and time; representations and ontologies for planning and scheduling; search methods and analysis of algorithms; formal characterisation of existing planners and schedulers.

Intelligent Agency: Resource-bounded reasoning; distributed problem solving; integrating reaction and deliberation.

Knowledge Engineering for Planning: Domain construction tools and techniques, knowledge elicitation, ontology development.

Learning: Learning in the context of planning and execution; learning new plans and operators; learning in the context of scheduling and schedule maintenance.

Memory Based Approaches: Case-based planning/scheduling; plan and operator learning and reuse; incremental planning.

Reactive Systems: Environmentally driven devices/behaviours; reactive control; behaviours in the context of minimal representations; schedule maintenance.

Robotics: Motion and path planning; planning and control; planning and perception, integration of planning and perceptual systems.

Constraint-based Planning/Scheduling and Control Techniques: Constraint/preference propagation techniques, variable/value ordering heuristics, intelligent backtracking/RMS-based techniques, iterative repair heuristics, etc.

Coordination Issues in Decentralised/Distributed planning/scheduling: Coordination issues in both homogeneous and heterogeneous systems, system architecture issues, integration of strategic and tactical decision making; collaborative planning/scheduling.

Iterative Improvement Techniques for Combinatorial Optimisation: Genetic algorithms, simulated annealing, tabu search, neural nets, etc applied to scheduling and/or planning..

Artificial Intelligence and Operations Research: Comparative studies and innovative applications combining AI and OR techniques applied to scheduling and/or planning.

Planning/scheduling under uncertainty: Coping with uncertain, ill-specified or changing domains, environments and problems; application of uncertainty reasoning techniques to planning/scheduling, including MDPs, POMDPs, Belief Networks, stochastic programming, and stochastic satisfiability.