Computational Intelligence: The Legacy of Alan Turing and John von Neumann

In this chapter fundamental problems of collaborative computational intelligence are discussed. The problems are distilled from the seminal research of Alan Turing and John von Neumann. For Turing the creation of machines with human-like intelligence was only a question of programming time. In his research he identified the most relevant problems concerning evolutionary computation, learning, and structure of an artificial brain. Many problems are still unsolved, especially efficient higher learning methods which Turing called initiative. Von Neumann was more cautious. He doubted that human-like intelligent behavior could be described unambiguously in finite time and finite space. Von Neumann focused on self-reproducing automata to create more complex systems out of simpler ones. An early proposal from John Holland is analyzed. It centers on adaptability and population of programs. The early research of Newell, Shaw, and Simon is discussed. They use the logical calculus to discover proofs in logic. Only a few recent research projects have the broad perspectives and the ambitious goals of Turing and von Neumann. As examples the projects Cyc, Cog, and JANUS are discussed.

[1]  Barry McMullin,et al.  John von Neumann and the Evolutionary Growth of Complexity: Looking Backward, Looking Forward , 2000, Artificial Life.

[2]  Michael J. Witbrock,et al.  Common Sense Reasoning - From Cyc to Intelligent Assistant , 2006, Ambient Intelligence in Everyday.

[3]  J. von Neumann,et al.  Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components , 1956 .

[4]  Allen Newell,et al.  Heuristic Problem Solving: The Next Advance in Operations Research , 1958 .

[5]  Douglas B. Lenat,et al.  CYC: a large-scale investment in knowledge infrastructure , 1995, CACM.

[6]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[7]  J. C. Shaw,et al.  Empirical explorations of the logic theory machine: a case study in heuristic , 1899, IRE-AIEE-ACM '57 (Western).

[8]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[9]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[10]  F. R. A. Hopgood,et al.  Machine Intelligence 6 , 1972, The Mathematical Gazette.

[11]  John von Neumann,et al.  Theory Of Self Reproducing Automata , 1967 .

[12]  Julio Abascal,et al.  Ambient Intelligence in Everyday Life , 2006, Lecture Notes in Computer Science.

[13]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[14]  J. Eccles The human mystery , 1978 .

[15]  John H. Holland,et al.  Iterative circuit computers , 1960, IRE-AIEE-ACM '60 (Western).

[16]  Arthur W. Burks,et al.  Essays on cellular automata , 1970 .

[17]  Uwe Beyer,et al.  Data exploration with reflective adaptive models , 1996 .

[18]  Heinz Mühlenbein,et al.  Towards A Theory of Organisms and Evolving Automata , 2004 .

[19]  John H. Holland,et al.  Outline for a Logical Theory of Adaptive Systems , 1962, JACM.

[20]  Rodney A. Brooks,et al.  From earwigs to humans , 1997, Robotics Auton. Syst..

[21]  J. R. Newman The World of Mathematics , 1961 .

[22]  R. Brooks,et al.  The cog project: building a humanoid robot , 1999 .

[23]  Frank J. Smieja,et al.  The pandemonium system of reflective agents , 1996, IEEE Trans. Neural Networks.

[24]  Chrystopher L. Nehaniv Computation for Metaphors, Analogy, and Agents , 2000, Lecture Notes in Computer Science.

[25]  S. P. Springer,et al.  Left brain, right brain , 1981 .

[26]  O. G. Selfridge,et al.  Pandemonium: a paradigm for learning , 1988 .

[27]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[28]  Anil Menon Frontiers of Evolutionary Computation , 2004 .

[29]  H. Simon,et al.  Models of My Life , 1991 .

[30]  Uwe Beyer,et al.  Learning from Examples, Agent Teams and the Concept of Reflection , 1996, Int. J. Pattern Recognit. Artif. Intell..