There are many algorithms for reinforcement learning, both model-based (e.g. dynamic programming) and model-free (e.g. Monte Carlo ... weights in its value and policy networks.

There are many different types of reinforcement learning algorithms, but two main categories are “model-based” and “model-free” RL. They are both inspired by our understanding of learning ...

Research team from Nanjing University proposed FOCUS, a causal model-based offline RL algorithm, which uses causal structure ...

Q-learning is a model-free, value-based, off-policy algorithm for reinforcement learning that will find the best series of actions based on the current state. The “Q” stands for quality.

A new study on meta reinforcement learning algorithms helps us understand ... space uncertainty in the arbitration between model-based and model-free learning." Human reinforcement learning ...

This study seeks to construct a basic reinforcement ... of unstable learning behaviours. This AI-macro model may be enhanced in future research by adding additional variables or sectors to the model ...