Nearly every book on reinforcement learning contains a chapter that explains the differences between model-free and model-based reinforcement learning.

The theoretical model employed by this team of researchers could soon be used by both theorists and computer scientists to further investigate the underpinnings of deep learning-based algorithms.

A comprehensive model of work-based learning is illustrated combining explicit and tacit forms of knowing and theory and practice modes of learning at both individual and collective levels. The model ...

Molnar's book also examines example-based explanations, which work by selecting particular instances of the dataset to explain model behavior or data distribution.

Based on our literature review, we identify current gaps in the research, including a lack of solid frameworks to explain learning in open online setting. Finally, we put forward a novel framework ...

Two major studies demonstrate the effectiveness of problem-based learning and show that students, parents and teachers prefer such immersive learning techniques.