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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 ...

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...

Reinforcement learning (RL) represents a paradigm shift in process control, offering adaptive and data‐driven strategies for the management and optimisation of complex industrial processes. By ...

AI coding tools are getting better fast. If you don’t work in code, it can be hard to notice how much things are changing, but GPT-5 and Gemini 2.5 have made a whole new set of developer tricks ...

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...

Prior deep learning experience (e.g. ELEC_ENG/COMP_ENG 395/495 Deep Learning Foundations from Scratch ) and strong familiarity with the Python programming language. Python will be used for all coding ...

Progress in self-­driving cars and other forms of automation will slow dramatically unless machines can hone skills through experience. Inside a simple computer simulation, a group of self-driving ...