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 ...

The "reward-is-enough" hypothesis suggests that reinforcement learning alone could lead to AGI.

One of the most interesting AI trends is the convergence of reinforcement learning with supervised and unsupervised learning in more advanced applications.

Matthew Dixon and Igor Halperin develop a reinforcement learning (RL) approach to goal-based wealth management problems such as optimisation of retirement plans or target date funds. They present ...

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

A novel real-time automated damage detection method leveraging reinforcement learning has been unveiled in a recent study ...

Central to the operational efficiency of HEVs is the Energy Management Strategy (EMS), which determines how power is ...