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 ...

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

Negative reinforcement encourages specific behaviors by removing or avoiding negative consequences or stimuli. It is different than punishment, which aims to discourage a specific behavior. Negative ...

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 ...

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 ...

Another one of my pet peeves is the fact that many people – civilians and scientists alike – use the phrase “negative reinforcement” to mean “punishment.” The two are not at all the same; in fact, ...

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

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 ...

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 ...