In the book "Weak intelligence" (see ttp://www.amazon.com/exec/obidos/ASIN/1560728981/qid%3D997700455/103-1711169-7916644) a tentative explanation is provided. It is claimed that the major thinking power comes from interactions between multiple subprocesses. The principle of "multiple knowledge", in a way similar to the Heisenberg principle, is introduced to divide nonintelligent and intelligent thinking (http://ai.ijs.si/mezi/weakAI/weakStrongAI.htm).

M. Gams: Weak intelligence: Through the principle and paradox of multiple knowledge, Advances in computation: Theory and practice, Volume 6, Nova science publishers, inc., NY, ISBN 1-56072-898-1, pp. 245, 2001.

CONTENTS (excerpts)

1.1 Artificial Intelligence Directions

1.2 History of Artificial Intelligence

1.3 Where's the AI?

1.4 Storage/Memory vs. Processing/Thinking

1.5 Problems with Formalistic AI

1.6 Strong-AI Super-Projects

4.1 Description

4.2 Sloman's Engineering Gradation of Strong-Weak AI

5.1 Alan Turing

5.2 The Turing Test

5.3 Turing Machine and Church-Turing Thesis

5.4 Church-Turing Thesis and Turing Machines

5.5 Goedel's Theorem and the Halting Problem

5.6 Penrose's Analyses of Goedel's Theorem

5.7 Is Interaction Stronger than Algorithms?

6.1 Basic Definitions

6.2 The Principle of Multiple Knowledge

6.3 The Paradox of Multiple Knowledge

7.1 Multiple Knowledge in Empirical Learning

7.2 Simulated Multiple Models

7.3 Formal Worst-Case Analyses

7.4 Formal Average-Case Improvements

7.5 Fitting the Model to Real-Life Applications

7.6 Human Multiple Reasoning

7.7 Cognitive Sciences and Common Sense

8.1 Occam's Razor Vs. Multiple Knowledge

8.2 Bayes' Classifier And Multiple Knowledge

8.3 Properties of Knowledge

9.1 Paradoxes of Modern Physics

9.2 Interpretations of Quantum Physics

9.3 The Many-Worlds Theory

9.4 Objections to the Many-Worlds Interpretation

9.4 Quantum Computing

9.5 From Many Worlds to the Principle of Multiple Knowledge