Improving Plan Quality through Heuristics for Guiding and Pruning the Search: A Study Using LAMA. - Francesco Percassi; Alfonso Emilio Gerevini; Hector Geffner (SOCS, 2017)

Iterative Width Search for Multi Agent Privacy-Preserving Planning. - Gabriele Bazzotti; Alfonso Emilio Gerevini; Nir Lipovetzky; Francesco Percassi; Alessandro Saetti; Ivan Serina (AI*IA, 2018)

Best-First Width Search for Multi Agent Privacy-Preserving Planning. - Alfonso Emilio Gerevini; Nir Lipovetzky; Francesco Percassi; Alessandro Saetti; Ivan Serina (ICAPS, 2019)

On Compiling Away PDDL3 Soft Trajectory Constraints without Using Automata. - Francesco Percassi; Alfonso Emilio Gerevini (ICAPS, 2019)

Novelty Messages Filtering for Multi Agent Privacy-Preserving Plannin. - Alfonso Emilio Gerevini; Nir Lipovetzky; Nico Peli; Francesco Percassi; Alessandro Saetti; Ivan Serina (SOCS, 2019)

Novelty Messages Filtering for Multi Agent Privacy-preserving Planning. - Alfonso Emilio Gerevini; Nir Lipovetzky; Nico Peli; Francesco Percassi; Alessandro Saetti; Ivan Serina (CoRR, 2019)

Generating and Exploiting Cost Predictions in Heuristic State-Space Planning. - Francesco Percassi; Alfonso Emilio Gerevini; Enrico Scala; Ivan Serina; Mauro Vallati (ICAPS, 2020)

A Sound (But Incomplete) Polynomial Translation from Discretised PDDL+ to Numeric Planning. - Francesco Percassi; Enrico Scala; Mauro Vallati (AI*IA, 2021)

On Planning with Qualitative State-Trajectory Constraints in PDDL3 by Compiling them Away. - Luigi Bonassi; Alfonso Emilio Gerevini; Francesco Percassi; Enrico Scala (ICAPS, 2021)

Translations from Discretised PDDL+ to Numeric Planning. - Francesco Percassi; Enrico Scala; Mauro Vallati (ICAPS, 2021)

The Power of Reformulation: From Validation to Planning in PDDL+. - Francesco Percassi; Enrico Scala; Mauro Vallati (ICAPS, 2022)

On the Use of Width-Based Search for Multi Agent Privacy-Preserving Planning (Extended Abstract). - Alfonso Emilio Gerevini; Nir Lipovetzky; Francesco Percassi; Alessandro Saetti; Ivan Serina (SOCS, 2022)

On the Reformulation of Discretised PDDL+ to Numeric Planning (Extended Abstract). - Francesco Percassi; Enrico Scala; Mauro Vallati (SOCS, 2022)

Goal Recognition as a Deep Learning Task: the GRNet Approach. - Mattia Chiari; Alfonso Emilio Gerevini; Luca Putelli; Francesco Percassi; Ivan Serina (CoRR, 2022)

A Structure-Sensitive Translation from Hybrid to Numeric Planning. - Francesco Percassi; Enrico Scala; Mauro Vallati (AI*IA, 2023)

Goal Recognition as a Deep Learning Task: The GRNet Approach. - Mattia Chiari; Alfonso Emilio Gerevini; Francesco Percassi; Luca Putelli; Ivan Serina; Matteo Olivato (ICAPS, 2023)

Fixing Plans for PDDL+ Problems: Theoretical and Practical Implications. - Francesco Percassi; Enrico Scala; Mauro Vallati (ICAPS, 2023)

Automated Planning for Generating and Simulating Traffic Signal Strategies. - Saumya Bhatnagar; Rongge Guo; Keith McCabe; Thomas L. McCluskey; Francesco Percassi; Mauro Vallati (IJCAI, 2023)

An Efficient Heuristic for AI-based Urban Traffic Control. - Francesco Percassi; Saumya Bhatnagar; Rongge Guo; Keith McCabe; Thomas Leo McCluskey; Mauro Vallati (MT-ITS, 2023)

On the Notion of Fixability of PDDL+ Plans [Extended Abstract]. - Francesco Percassi; Enrico Scala; Mauro Vallati (SOCS, 2023)

A Practical Approach to Discretised PDDL+ Problems by Translation to Numeric Planning. - Francesco Percassi; Enrico Scala; Mauro Vallati (J. Artif. Intell. Res., 2023)

Width-based search for multi agent privacy-preserving planning. - Alfonso Emilio Gerevini; Nir Lipovetzky; Francesco Percassi; Alessandro Saetti; Ivan Serina (Artif. Intell., 2023)

Improving Domain-Independent Heuristic State-Space Planning via plan cost predictions. - Francesco Percassi; Alfonso Emilio Gerevini; Enrico Scala; Ivan Serina; Mauro Vallati (J. Exp. Theor. Artif. Intell., 2023)

An Effective Polynomial Technique for Compiling Conditional Effects Away. - Alfonso Emilio Gerevini; Francesco Percassi; Enrico Scala (AAAI, 2024)

An Extensive Empirical Analysis of Macro-actions for Numeric Planning. - Diaeddin Alarnaouti; Francesco Percassi; Mauro Vallati (AI*IA, 2024)

The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis on a Real-world Case Study. - Anas El Kouaiti; Francesco Percassi; Alessandro Saetti; Mauro Vallati (FLAIRS, 2024)

Taming Discretised PDDL+ through Multiple Discretisations. - Matteo Cardellini; Marco Maratea; Francesco Percassi; Enrico Scala; Mauro Vallati (ICAPS, 2024)

PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation. - Anas El Kouaiti; Francesco Percassi; Alessandro Saetti; Thomas Leo McCluskey; Mauro Vallati (ICAPS, 2024)

Optimising Traffic Flow Through Synchronised Signal Configurations Along Urban Corridors. - Rongge Guo; Francesco Percassi; Mauro Vallati (ITSC, 2024)

Leveraging AI Planning in a What-If Analysis Framework for Assessing Traffic Signal Strategies. - Francesco Percassi; Mauro Vallati (ITSC, 2024)

Taming Discretised PDDL+ through Multiple Discretisations (Extended Abstract). - Matteo Cardellini; Marco Maratea; Francesco Percassi; Enrico Scala; Mauro Vallati (SOCS, 2024)

Deployable Yet Effective Traffic Signal Optimisation via Automated Planning (Extended Abstract). - Anas El Kouaiti; Francesco Percassi; Alessandro Saetti; Thomas Leo McCluskey; Mauro Vallati (SOCS, 2024)

Optimised Variants of Polynomial Compilation for Conditional Effects in Classical Planning. - Francesco Percassi; Enrico Scala; Alfonso Emilio Gerevini (SOCS, 2024)

Towards Practical Classical Planning Compilations of Numeric Planning. - Luigi Bonassi; Francesco Percassi; Enrico Scala (AAAI, 2025)

Automated Planning for Urban Traffic Control with LLM-Generated Configurations. - Francesco Percassi; Mauro Vallati (FLAIRS, 2025)