Creating A Memory of Causal Relationships: An Integration of Empirical and Explanation-based Learning Methods

This book presents a theory of learning new causal relationships by making use of perceived regularities in the environment, general knowledge of causality, and existing causal knowledge. Integrating ideas from the psychology of causation and machine learning, the author introduces a new learning procedure called theory-driven learning that uses abstract knowledge of causality to guide the induction process.

Known as OCCAM, the system uses theory-driven learning when new experiences confor...