Tesh (Natalia)

Tesh Natalia, a researcher at OIST with a unique blend of theoretical chemistry and cognitive science, dives into Hopfield networks and their capacity to tackle propositional satisfiability problems. She explains the dynamics of these networks and how they can optimize memory through Hebbian learning. Tesh also discusses their potential to connect agent beliefs and preferences to behavioral controls, and explores the implications for creativity, learning, and decision-making in simulated environments. Fascinating insights into artificial intelligence and cognition unfold throughout!