Ronen I. Brafman
Papers
9
Total Citations
139
H-Index
7
About
Ronen I. Brafman is a leading figure in automated planning, scheduling, and robotics, whose work bridges formal logic and practical control under uncertainty. His seminal contributions center on applying logics of knowledge—borrowed from distributed computing—to motion planning, enabling robots to reason about what they know and need to know in uncertain environments. His 1997 paper on this topic (36 citations) and related works (e.g., 1998, 17 citations) established a high-level abstraction for analyzing informational requirements of robotic tasks, introducing concepts like knowledge complexity. Brafman also shaped the field through his role in the 20th International Conference on Automated Planning and Scheduling (ICAPS’10, 31 citations), which showcased advances in planning under uncertainty and search algorithms. More recently, he has explored performance-level profiles for robot controllers (2016, 9 citations) and parameter tuning via deep reinforcement learning (2023, 4 citations). With a career spanning foundational theory to applied AI, Brafman’s work has influenced how robots handle incomplete information, making him a key thinker for students and researchers in autonomous systems and decision-making.
Research Focus
Key Achievements
Top Papers
- 1Applications of a logic of knowledge to motion planning under uncertainty36 citations · 1997
- 2
- 3On the knowledge requirements of tasks17 citations · 1998
- 4Knowledge considerations in robotics and distribution of robotic tasks14 citations · 1995
- 5Knowledge as a Tool in Motion Planning under Uncertainty13 citations · 1994
- 6Towards knowledge-level analysis of motion planning11 citations · 1993
- 7
- 8PTDRL: Parameter Tuning Using Deep Reinforcement Learning4 citations · 2023
- 9Knowledge considerations in robotics4 citations · 1996