And we have much more than just model-free and model-based reinforcement learning, Lee believes. “I think our brain is a pandemonium of learning algorithms that have evolved to handle many ...

Model-based algorithms: Model-based algorithms take a different approach to reinforcement learning. Instead of evaluating the value of states and actions, they try to predict the state of the ...

Model-based algorithms: Model-based algorithms take a different approach to reinforcement learning. Instead of evaluating the value of states and actions, they try to predict the state of the ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output adjustments, according to a study led by University of Michigan researchers, ...

AI algorithms for deep-reinforcement learning have demonstrated the ability to learn at very high levels in constrained domains.

Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural ...