Enrico Scala
Papers
3
Total Citations
12
H-Index
2
About
Enrico Scala is a researcher at the forefront of AI planning, specializing in robust plan execution and the intricate challenges of planning for hybrid systems. His work addresses a fundamental problem in artificial intelligence: how to ensure that plans remain executable in the unpredictable real world. Scala’s major contribution lies in developing frameworks that allow agents—whether software or robotic—to dynamically reconfigure and replan when unexpected contingencies arise, moving beyond simple propositional goals to handle complex time constraints. His most cited work, "Robust plan execution via reconfiguration and replanning" (2015, 8 citations), provides a foundational approach for maintaining plan integrity during execution. More recently, his research on "AI Planning for Hybrid Systems" (2023) tackles the sophisticated modeling required for physical entities, such as robots, whose states evolve according to non-linear dynamics. This work is critical for bridging the gap between high-level task planning and low-level continuous control. Scala also contributed to the STEPS project, developing a predictive and command system for an EVA Rescue Use Case, demonstrating his commitment to applying theoretical advances to tangible, high-stakes applications.
Research Focus
Key Achievements
Top Papers
- 1Robust plan execution via reconfiguration and replanning8 citations · 2015
- 2AI Planning for Hybrid Systems2 citations · 2023
- 3STEPS: PCS results on 1st working prototype2 citations · 2010