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Francesco Percassi

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2020 – today

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2024
[c25]
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Alfonso Emilio Gerevini, Francesco Percassi, Enrico Scala:
An Effective Polynomial Technique for Compiling Conditional Effects Away. AAAI 2024: 20104-20112
[c24]
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Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Mauro Vallati:
The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis on a Real-world Case Study. FLAIRS 2024
[c23]
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Matteo Cardellini, Marco Maratea, Francesco Percassi, Enrico Scala, Mauro Vallati:
Taming Discretised PDDL+ through Multiple Discretisations. ICAPS 2024: 59-67
[c22]
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Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Thomas Leo McCluskey, Mauro Vallati:
PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation. ICAPS 2024: 168-177
[c21]
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Francesco Percassi, Enrico Scala, Alfonso Emilio Gerevini:
Optimised Variants of Polynomial Compilation for Conditional Effects in Classical Planning. SOCS 2024: 100-108
[c20]
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Matteo Cardellini, Marco Maratea, Francesco Percassi, Enrico Scala, Mauro Vallati:
Taming Discretised PDDL+ through Multiple Discretisations (Extended Abstract). SOCS 2024: 263-264
[c19]
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Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Thomas Leo McCluskey, Mauro Vallati:
Deployable Yet Effective Traffic Signal Optimisation via Automated Planning (Extended Abstract). SOCS 2024: 269-270
2023
[j3]
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  - journals/ai/GereviniLPSS23
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Alfonso Emilio Gerevini, Nir Lipovetzky, Francesco Percassi, Alessandro Saetti, Ivan Serina:
Width-based search for multi agent privacy-preserving planning. Artif. Intell. 318: 103883 (2023)
[j2]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
A Practical Approach to Discretised PDDL+ Problems by Translation to Numeric Planning. J. Artif. Intell. Res. 76: 115-162 (2023)
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Francesco Percassi, Alfonso Emilio Gerevini, Enrico Scala, Ivan Serina, Mauro Vallati:
Improving Domain-Independent Heuristic State-Space Planning via plan cost predictions. J. Exp. Theor. Artif. Intell. 35(6): 849-875 (2023)
[c18]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
A Structure-Sensitive Translation from Hybrid to Numeric Planning. AI*IA 2023: 105-118
[c17]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
Fixing Plans for PDDL+ Problems: Theoretical and Practical Implications. ICAPS 2023: 324-333
[c16]
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  - conf/aips/ChiariGPPSO23
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Mattia Chiari, Alfonso Emilio Gerevini, Francesco Percassi, Luca Putelli, Ivan Serina, Matteo Olivato:
Goal Recognition as a Deep Learning Task: The GRNet Approach. ICAPS 2023: 560-568
[c15]
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  - conf/ijcai/BhatnagarGMMPV23
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Saumya Bhatnagar, Rongge Guo, Keith McCabe, Thomas L. McCluskey, Francesco Percassi, Mauro Vallati:
Automated Planning for Generating and Simulating Traffic Signal Strategies. IJCAI 2023: 7119-7122
[c14]
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Francesco Percassi, Saumya Bhatnagar, Rongge Guo, Keith McCabe, Thomas Leo McCluskey, Mauro Vallati:
An Efficient Heuristic for AI-based Urban Traffic Control. MT-ITS 2023: 1-6
[c13]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
On the Notion of Fixability of PDDL+ Plans [Extended Abstract]. SOCS 2023: 177-178
2022
[c12]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
The Power of Reformulation: From Validation to Planning in PDDL+. ICAPS 2022: 288-296
[c11]
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Alfonso Emilio Gerevini, Nir Lipovetzky, Francesco Percassi, Alessandro Saetti, Ivan Serina:
On the Use of Width-Based Search for Multi Agent Privacy-Preserving Planning (Extended Abstract). SOCS 2022: 276-278
[c10]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
On the Reformulation of Discretised PDDL+ to Numeric Planning (Extended Abstract). SOCS 2022: 314-316
[i3]
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  - journals/corr/abs-2210-02377
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Mattia Chiari, Alfonso Emilio Gerevini, Luca Putelli, Francesco Percassi, Ivan Serina:
Goal Recognition as a Deep Learning Task: the GRNet Approach. CoRR abs/2210.02377 (2022)
2021
[c9]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
A Sound (But Incomplete) Polynomial Translation from Discretised PDDL+ to Numeric Planning. AI*IA 2021: 18-31
[c8]
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  - conf/aips/BonassiGPS21
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Luigi Bonassi, Alfonso Emilio Gerevini, Francesco Percassi, Enrico Scala:
On Planning with Qualitative State-Trajectory Constraints in PDDL3 by Compiling them Away. ICAPS 2021: 46-50
[c7]
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Francesco Percassi, Enrico Scala, Mauro Vallati:
Translations from Discretised PDDL+ to Numeric Planning. ICAPS 2021: 252-261
2020
[c6]
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Francesco Percassi, Alfonso Emilio Gerevini, Enrico Scala, Ivan Serina, Mauro Vallati:
Generating and Exploiting Cost Predictions in Heuristic State-Space Planning. ICAPS 2020: 569-573

2010 – 2019

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2019
[c5]
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Alfonso Emilio Gerevini, Nir Lipovetzky, Francesco Percassi, Alessandro Saetti, Ivan Serina:
Best-First Width Search for Multi Agent Privacy-Preserving Planning. ICAPS 2019: 163-171
[c4]
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Francesco Percassi, Alfonso Emilio Gerevini:
On Compiling Away PDDL3 Soft Trajectory Constraints without Using Automata. ICAPS 2019: 320-328
[c3]
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Alfonso Emilio Gerevini, Nir Lipovetzky, Nico Peli, Francesco Percassi, Alessandro Saetti, Ivan Serina:
Novelty Messages Filtering for Multi Agent Privacy-Preserving Plannin. SOCS 2019: 79-87
[i2]
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  - journals/corr/abs-1906-03955
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Alfonso Emilio Gerevini, Nir Lipovetzky, Francesco Percassi, Alessandro Saetti, Ivan Serina:
Best-First Width Search for Multi Agent Privacy-preserving Planning. CoRR abs/1906.03955 (2019)
[i1]
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  - journals/corr/abs-1906-08061
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Alfonso Emilio Gerevini, Nir Lipovetzky, Nico Peli, Francesco Percassi, Alessandro Saetti, Ivan Serina:
Novelty Messages Filtering for Multi Agent Privacy-preserving Planning. CoRR abs/1906.08061 (2019)
2018
[c2]
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  - conf/aiia/BazzottiGLPSS18
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Gabriele Bazzotti, Alfonso Emilio Gerevini, Nir Lipovetzky, Francesco Percassi, Alessandro Saetti, Ivan Serina:
Iterative Width Search for Multi Agent Privacy-Preserving Planning. AI*IA 2018: 431-444
2017
[c1]
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  - conf/socs/PercassiGG17
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Francesco Percassi, Alfonso Emilio Gerevini, Hector Geffner:
Improving Plan Quality through Heuristics for Guiding and Pruning the Search: A Study Using LAMA. SOCS 2017: 144-148

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