From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...

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 ...

With the rapid advancement of Large Language Models (LLMs), an increasing number of researchers are focusing on Generative Recommender Systems (GRSs). Unlike traditional recommendation systems that ...

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 ...

Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...

If you walk down the street shouting out the names of every object you see — garbage truck! bicyclist! sycamore tree! — most people would not conclude you are smart. But if you go through an obstacle ...

Positive reinforcement involves rewarding an employee for doing a good job. An example would be giving an employee a paid vacation day for exceeding monthly production goals. Negative reinforcement ...

Negative reinforcement is sometimes confused with punishment, but in the workplace, negative reinforcement can be an effective tool for motivating employee behavior when done in an appropriate anner.