Aim of the Workshop

Automated Planning and Ontology are two well-established fields of Artificial Intelligence (AI). The former investigates techniques to formally model and reason about the effects of actions, and decide the combinations of actions that allow an agent to achieve goals. The latter investigates techniques to formally define knowledge (by formally describing domain entities and their interrelations), allowing agents to process information about objects, and events, and incrementally build and verify beliefs.

Both Automated Planning and Ontology generally rely on logic to model knowledge and organize reasoning mechanisms. They support the development of cognitive capabilities that autonomous agents need to effectively act in the real world. In this context, the PLanning And onTology wOrkshop (PLATO) aims at bringing together researchers in these two fields of AI to address new research challenges, share their experiences, and learn from each other.

The workshop aims at investigating the synergetic contributions of technologies and methods from these two fields. There are examples in the literature that have investigated the use of Ontology to generate planning models, find effective plans, and contextualize plans and action execution to domain features.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Short papers - 6 pages (including references) formatted as LNCS one-column paper. These should describe concrete problems, open issues concerning planning and ontology, or methodologies/approaches pointing out the added values of the integration between planning and ontology.
• Full papers - 13 pages (including references) formatted as LNCS one-column paper. These should report work-in-progress, novel designed technologies or systems relying on the integration of panning and ontology.

List of Topics

• Ontological analysis of concepts related to planning/scheduling (e.g., capability, capacity, action, etc)
• Domain ontologies supporting tasks related to planning/scheduling
• Reuse of foundational ontologies (e.g., DOLCE, BFO, UFO) in order to strive the interoperability among multiple ontologies, among other goals  
• Semantic Web ontologies and technologies for reasoning, (FAIR) data management, interoperability, etc
• Ontologies supporting the interoperability of heterogeneous planning frameworks
• Ontologies supporting Plan and Schedule Execution
• Plan Recognition, plan management, and goal reasoning
• Partially observable and unobservable domains
• Knowledge acquisition and engineering for planning and scheduling
• Situation assessment for contextualized planning decisions
• Explainability of plans and planning models
• Trustworthy, safety, and ethics in planning
• Benchmarking and evaluation metrics of plans and plan-based controllers
• Out-of-the-box research challenges at the intersection between Automated Planning and Ontology

Committees

Program Committee (to be extended)

• Iman Awaad, Bonn-Rhein-Sieg University, Germany
• Daniel Bessler, University of Bremen, Germany
• Stefano Borgo, CNR-ISTC, Italy
• Chiara Di Francescoromano, University of Trento, Italy
• Lucia Goméz Alvaréz, TU Dresden, Germany
• Masoumeh Iran Mansouri, University of Birmingham, UK
• Marianna Nicolosi Asmundo, University of Catania, Italy
• Andrea Orlandini, CNR-ISTC, Italy
• Ron Petrick, Herriot-Watt University, UK
• Daniele Francesco Santamaria, University of Catania, Italy
• Guillaume Sarthou, LAAS CNRS, France
• Uil Sattler, University of Manchester, UK
• Biplav Srivastava, University of South Carolina, USA
• Walter Terkaj, CNR-STIIMA, Italy
• Mauro Vallati, University of Huddersfield, UK

Organizing committee

• Emilio M. Sanfilippo, CNR-ISTC, Italy
• Alessandro Umbrico, CNR-ISTC, Italy

Contact

For inquiries please send an email to <plato2023 AT easychair.org>