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 ...

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 ...

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 ...

The age of truly autonomous artificial intelligence, where systems proactively learn, adapt and optimize amid real-world complexities instead of simply reacting, has been a long-held aspiration. Now, ...

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 ...

If you replay arguments long after they end, your brain may be seeking reward, not resolution. Here’s how dopamine shapes ...

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 ...

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, ...

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 ...