Effective approaches for handling temporal constraints in automated planning problems
My research activity focuses on developing effective and efficient systems to deal with complex temporal constraints in automated planning problems. Specifically, I'm developing compilation-based approaches to handle state-trajectory and action-trajectory constraints. These constraints are temporal properties that every plan must satisfy. Our approach consists in compiling a planning problem featuring such constraints into a classical planning problem that can be solved by any state-of-the-art classical planner.
ADVISOR(S):
- Primary: Alfonso Gerevini
- Other advisors: Enrico Scala
RESEARCH:
- Research group: Intelligenza Artificiale, Interazione Uomo-Macchina e Robotica
- Curriculum: Computer Science/Engineering and Control Systems
- List of publications: IRIS UNIBS
CONTACTS:
Short Bio
I was born in Brescia (Italy) on the 13th of October, 1995. I received the Bs.c in computer science and engineering in 2018 with the final grade of 110/110 cum laude at Università degli Studi di Brescia with a thesis titled "Analysis of advanced techniques for NUMA architectures". I then achieved my Master’s degree in computer science and engineering in 2020 with the final grade of 110/110 cum laude at Università degli Studi di Brescia. My master thesis was titled "Compilation-based approaches for handling state trajectory constraints in planning problems". I am currently a Ph.D. student in Information Engineering at Università degli Studi di Brescia.