Quantifying inductive bias: AI learning algorithms and Valiant's learning framework

• RL can be used to solve problems involving sequential decision-making.
• RL is based on trial-and-error learning through rewards and punishments.
• The ultimate goal of an RL agent is to maximize cumulative reward.
• RL agent tries ...

Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential decision-making in complex problems. RL is inspired by trial-and-error based human/animal learning. It can learn an optimal policy autonomously with knowledge ...

This research shows that inductive bias provides a valuable method to effectively tackle semi-supervised classification problems. In the learning theory framework, inductive bias provides a powerful tool, and allows one to shape the generalization ...