Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Reinforcement-learning algorithms 1,2 are inspired by our understanding of decision making in humans and other animals in which learning is supervised through the use of reward signals in response to ...

Negative reinforcement is a method that can be used to help teach specific behaviors. With negative reinforcement, something uncomfortable or otherwise unpleasant is taken away in response to a ...

Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...

ChatGPT and other AI tools are upending our digital lives, but our AI interactions are about to get physical. Humanoid robots trained with a particular type of AI to sense and react to their world ...

The Reinforcement Theory, with its nuanced understanding of human behavior, offers leaders a structured approach to drive desired behaviors, invigorate teams, and sculpt an organizational culture that ...

Nearly a century ago, psychologist B.F. Skinner pioneered a controversial school of thought, behaviorism, to explain human and animal behavior. Behaviorism directly inspired modern reinforcement ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

Scottish philosopher James Beattie said a mouthful when he observed that "in every age and every man, there is something to praise as well as to blame." In other words, people face a choice when ...