Carl B. Frankel
Papers
2
Total Citations
39
H-Index
2
About
Carl B. Frankel is a pioneering researcher in cognitive robotics, with a primary focus on enabling robots to learn and internalize affordance relations—the actionable possibilities objects offer in an environment. His major contribution lies in developing a novel framework where robots use internal rehearsal, a form of simulated practice, to learn general affordance relations from their own experiences. This approach models affordances as statistical relationships between actions, object properties, and outcomes, allowing robots to predict and adapt without exhaustive real-world trials. Frankel’s most cited work, "Towards a cognitive robot that uses internal rehearsal to learn affordance relations" (2008), has garnered 31 citations, underscoring its influence in advancing robot cognition and autonomous learning. His subsequent paper, "A robot rehearses internally and learns an affordance relation" (2008), with 8 citations, further refines this methodology. Together, these works represent a foundational step toward creating robots that can reason, plan, and generalize like cognitive agents, bridging the gap between perception and action. Frankel’s research is a cornerstone for students and researchers interested in embodied cognition, machine learning, and the future of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2A robot rehearses internally and learns an affordance relation8 citations · 2008