Operant Conditioning

Operant conditioning, the learning process where behaviors are strengthened or weakened by consequences, remains a central topic in behavioral science and is increasingly informing artificial intelligence research. Current research focuses on developing computational models, such as those inspired by the hippocampus or employing reinforcement learning techniques within diffusion models, to better understand and replicate the adaptive learning capabilities observed in biological systems. This work aims to improve AI's ability to learn complex tasks efficiently and adapt to changing environments, with potential applications ranging from advanced robotics to personalized education. The insights gained are also furthering our understanding of the neural mechanisms underlying learning and behavior in animals and humans.