Induction and Physical Theory Formation As Well As Universal Computation by Machine Learning

Machine learning presents a general, systematic framework for the generation of formal theoretical models for physical description and prediction. Tentatively standard linear modelling techniques are reviewed; followed by a brief discussion of “swarm-intelligent” generalizations to deep forward networks for approximating nonlinear phenomena and universal computation.