Includes bibliographical references and index.

Preface -- Acknowledgement -- Introduction -- Rapid Unsupervised Effective Causal Learning -- A General Noological Framework -- Conceptual Grounding and Operational Representation -- Causal Rules, Problem Solving, and Operational Representation -- The Causal Role of Sensory Information -- Application to the StarCraft Game Environment -- A Grand Challenge for Noology and Computational Intelligence -- Affect Driven Noological Processes -- Summary and Beyond -- Appendix A: Causal vs Reinforcement Learning -- Appendix B: Rapid Effective Causal Learning Algorithm -- Index

The idea of this book is to establish a new scientific discipline, “noology,” under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems.
The methodology adopted in Principles of Noology for the characterization of intelligent systems, or “noological systems,” is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems.