This workshop aims at bringing together researchers interested in different aspects of planning and scheduling problems, and to introduce new researchers to the community.
Although the primary target of this series of workshops is the Italian community of P&S, the aim is to attract an international gathering, thus expecting contributions and participation from around the world.
Submissions to this event are here solicited. Each contribution will be reviewed by members of a strong international Program Committee. Original and already published papers will be made available via this workshop web-site.
September 20th October 4th, 2020
October 16th October 23rd, 2020
Camera-ready: October 30th, 2020
Video and slides of the presentation: November 10th, 2020
Workshop: November 25th-27th, 2020
Topics of Interest
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.
- Machine and Deep Learning: Machine and Deep Learning Techniques applied to scheduling and/or planning.
- 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.
- Hybrid Systems: planning with mixed discrete-continuous domains; hybrid systems applications; novel benchmark problems involving hybrid dynamics; hybrid planning domain modelling; plan validation and execution.
- 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.
We welcome two categories of paper submission:
Short papers (up to 7 pages). These should report views or ambitions, or describe problems. The author(s) will be able to discuss the paper informally with others at the workshop and will be invited to give a short presentation on their work.
Full papers (more than 7 pages). These should report work in progress or completed work. Authors of full papers that are accepted by the Programme Committee will be invited to give a talk on the paper.
Each paper has to be submitted in English, and formatted according to the Springer’s LNCS style.
IPS proceedings will be published in CEUR Workshop Proceedings series. Together with the AIxIA, the IPS organizing committee is investigating ways to publish the proceedings in a series of Lecture Notes in Artificial Intelligence (Springer). An opportunity to publish in this series is given to both short and long papers, provided that the work has not been published before and a proper revision of the content of the paper is done so as to meet LNAI standards. Original accepted papers will be submitted for indexation by: DBLP, Thomson Reuters, EI, SCOPUS, Semantic Scholar and Google Scholar.
Authors of already published papers must clearly indicate this information in their submission.
Paper submission will take place through the EasyChair web site.
We are investigating the possibility of a special issue of an international journal.