Ivan A. Potapov
Papers
3
Total Citations
22
H-Index
3
About
Ivan A. Potapov is a computational neuroscientist and robotics researcher whose work bridges the gap between biological neural mechanisms and artificial intelligence. His primary research areas include semantic knowledge representation, central pattern generators (CPGs), and biomorphic robotics. Potapov’s most significant contribution is his novel framework for semantic knowledge representation in strategic interactions, which models how evolved beings abstract meaning from actions to anticipate consequences in dynamic, multilevel situations—a concept with potential applications in AI decision-making and cognitive science. This work, published in 2020, has garnered 13 citations, reflecting its growing influence. He has also advanced the field of bio-inspired robotics by developing self-organizing CPGs using spiking neural networks, demonstrated in a biomorphic fish robot (2022, 6 citations). His 2023 model of a CPG incorporating diverse neuron types (3 citations) further refines our understanding of how locomotor patterns are generated and modulated by sensory feedback. Potapov’s research is notable for its interdisciplinary approach, merging neuroscience, AI, and robotics to create more adaptive and intelligent systems. His work holds promise for both theoretical insights into neural computation and practical applications in autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Self-organizing CPGs in the control loop of a biomorphic fish robot6 citations · 2022
- 3