Machine super intelligence

[1]  Shane Legg,et al.  Temporal Difference Updating without a Learning Rate , 2007, NIPS.

[2]  Jonathan Schaeffer,et al.  Checkers Is Solved , 2007, Science.

[3]  Marcus Hutter,et al.  Universal Algorithmic Intelligence: A Mathematical Top→Down Approach , 2007, Artificial General Intelligence.

[4]  L. Terman.  The measurement of intelligence , 2007 .

[5]  Shane Legg,et al.  Tests of Machine Intelligence , 2006, 50 Years of Artificial Intelligence.

[6]  Shane Legg,et al.  Fitness uniform optimization , 2006, IEEE Transactions on Evolutionary Computation.

[7]  Shane Legg,et al.  A Formal Measure of Machine Intelligence , 2006, ArXiv.

[8]  Marcus Hutter,et al.  Universal Learning of Repeated Matrix Games , 2005, ArXiv.

[9]  C. S. Wallace,et al.  Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics) , 2005 .

[10]  P. Vitányi,et al.  Clustering by compression , 2003, IEEE Transactions on Information Theory.

[11]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[12]  Marcus Hutter,et al.  Convergence of Discrete MDL for Sequential Prediction , 2004, COLT.

[13]  Jürgen Schmidhuber,et al.  Optimal Ordered Problem Solver , 2002, Machine Learning.

[14]  Varol Akman,et al.  Turing Test: 50 Years Later , 2000, Minds and Machines.

[15]  Hideyuki Nakashima,et al.  AI as Complex Information Processing , 1999, Minds and Machines.

[16]  Paul Schweizer,et al.  The Truly Total Turing Test* , 1998, Minds and Machines.

[17]  Peter Dayan,et al.  The convergence of TD(λ) for general λ , 1992, Machine Learning.

[18]  J. Hawkins,et al.  On Intelligence , 2004 .

[19]  A. Kaufman.  Tests of intelligence , 2004 .

[20]  Jürgen Schmidhuber,et al.  Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements , 2003, ArXiv.

[21]  John R. Koza,et al.  Genetic Programming IV: Routine Human-Competitive Machine Intelligence , 2003 .

[22]  J. Fuster.  Cortex and mind : unifying cognition , 2003 .

[23]  Steffen Christensen,et al.  The Turing Ratio: Metrics For Open-ended Tasks , 2002, GECCO.

[24]  S. S. Adams,et al.  Beyond the Turing test: performance metrics for evaluating a computer simulation of the human mind , 2002, Proceedings 2nd International Conference on Development and Learning. ICDL 2002.

[25]  L. Gottfredson.  G: Highly general and highly practical , 2002 .

[26]  Marcus Hutter,et al.  Fitness uniform selection to preserve genetic diversity , 2001, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[27]  Marcus Hutter.  The Fastest and Shortest Algorithm for all Well-Defined Problems , 2002, Int. J. Found. Comput. Sci..

[28]  Robert J. Sternberg,et al.  Dynamic Testing: The Nature and Measurement of Learning Potential , 2001 .

[29]  Marcus Hutter.  Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences , 2001, ECML.

[30]  J. Sattler.  Assessment of Children: Cognitive Applications , 2001 .

[31]  Ricardo R. Gudwin,et al.  Evaluating intelligence: a computational semiotics perspective , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[32]  José Hernández-Orallo,et al.  Beyond the Turing Test , 2000, J. Log. Lang. Inf..

[33]  J. Raven.  The Raven's Progressive Matrices: Change and Stability over Culture and Time , 2000, Cognitive Psychology.

[34]  M. Sur,et al.  Visual behaviour mediated by retinal projections directed to the auditory pathway , 2000, Nature.

[35]  R. Sternberg,et al.  Handbook of Intelligence , 2000 .

[36]  R. Kurzweil.  The age of spiritual machines: when computers exceed human intelligence , 1998 .

[37]  Christof Koch,et al.  Biophysics of Computation: Information Processing in Single Neurons (Computational Neuroscience Series) , 1998 .

[38]  Randy Goebel,et al.  Computational intelligence - a logical approach , 1998 .

[39]  David L. Dowe,et al.  A Non-Behavioural, Computational Extension to the Turing Test , 1998 .

[40]  T. Zentall.  Animal Memory: The Role of “Instructions” , 1997 .

[41]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[42]  L. Gottfredson.  Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography , 1997 .

[43]  L. Gottfredson.  Why g matters: The complexity of everyday life , 1997 .

[44]  Jason Hutchens,et al.  How to Pass the Turing Test by Cheating , 1997 .

[45]  Jorma Rissanen,et al.  Fisher information and stochastic complexity , 1996, IEEE Trans. Inf. Theory.

[46]  R. Sternberg,et al.  Intelligence: Knowns and unknowns. , 1996 .

[47]  D.B. Fogel.  Review of Computational Intelligence: Imitating Life [Book Reviews] , 1995, Proceedings of the IEEE.

[48]  Ben J. A. Kröse,et al.  Learning from delayed rewards , 1995, Robotics Auton. Syst..

[49]  R. Herrnstein,et al.  The bell curve : intelligence and class structure in American life , 1995 .

[50]  F. Hsu,et al.  Deep Blue system overview , 1995, ICS '95.

[51]  Frans M. J. Willems,et al.  The context-tree weighting method: basic properties , 1995, IEEE Trans. Inf. Theory.

[52]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[53]  Ian H. Witten,et al.  Objective evaluation of inferred context-free grammars , 1994, Proceedings of ANZIIS '94 - Australian New Zealnd Intelligent Information Systems Conference.

[54]  Stuart M. Shieber,et al.  Lessons from a restricted Turing test , 1994, CACM.

[55]  Cristian S. Calude.  Information and Randomness , 1994, Monographs in Theoretical Computer Science An EATCS Series.

[56]  J. Carroll.  Human Cognitive Abilities-a sur-vey of factor-analytic studies , 1993 .

[57]  W. Lewis Johnson.  Needed: a new test of intelligence , 1992, SGAR.

[58]  James S. Albus,et al.  Outline for a theory of intelligence , 1991, IEEE Trans. Syst. Man Cybern..

[59]  Moshe Abeles,et al.  Corticonics: Neural Circuits of Cerebral Cortex , 1991 .

[60]  Ian H. Witten,et al.  Text Compression , 1990, 125 Problems in Text Algorithms.

[61]  J. Bather,et al.  Multi‐Armed Bandit Allocation Indices , 1990 .

[62]  R. French.  Subcognition and the Limits of the TuringTest , 1990 .

[63]  R. L. Gregory,et al.  The Oxford companion to the mind , 1989 .

[64]  Stevan Harnad,et al.  Minds, machines and Searle , 1989, J. Exp. Theor. Artif. Intell..

[65]  Douglas B. Lenat,et al.  On the thresholds of knowledge , 1987, Proceedings of the International Workshop on Artificial Intelligence for Industrial Applications.

[66]  David E. Goldberg,et al.  Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.

[67]  R. Cattell.  Intelligence : its structure, growth and action , 1987 .

[68]  M. Minsky.  The Society of Mind , 1986 .

[69]  K. Gunderson.  Mentality and Machines , 1985 .

[70]  E. Macphail.  Vertebrate intelligence: the null hypothesis , 1985 .

[71]  Donald A. Berry,et al.  Bandit Problems: Sequential Allocation of Experiments. , 1986 .

[72]  R. Sternberg.  Beyond IQ: A Triarchic Theory of Human Intelligence , 1984 .

[73]  H. Gardner,et al.  Frames of Mind: The Theory of Multiple Intelligences , 1983 .

[74]  J. Rothwell.  Principles of Neural Science , 1982 .

[75]  H. Birx,et al.  The Mismeasure of Man , 1981 .

[76]  N. Block.  Psychologism and Behaviorism , 1981 .

[77]  John R. Searle,et al.  Minds, brains, and programs , 1980, Behavioral and Brain Sciences.

[78]  Ray J. Solomonoff,et al.  Complexity-based induction systems: Comparisons and convergence theorems , 1978, IEEE Trans. Inf. Theory.

[79]  Ian H. Witten,et al.  An Adaptive Optimal Controller for Discrete-Time Markov Environments , 1977, Inf. Control..

[80]  Allen Newell,et al.  Computer science as empirical inquiry: symbols and search , 1976, CACM.

[81]  L. Resnick.  The Nature of Intelligence , 2024 .

[82]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[83]  B. Slotnick,et al.  Olfactory Learning-Set Formation in Rats , 1974, Science.

[84]  M. A. Merrill,et al.  Stanford-Binet Intelligence Scale , 1972 .

[85]  J. M. Barzdin,et al.  Prognostication of Automata and Functions , 1971, IFIP Congress.

[86]  L. Levin,et al.  THE COMPLEXITY OF FINITE OBJECTS AND THE DEVELOPMENT OF THE CONCEPTS OF INFORMATION AND RANDOMNESS BY MEANS OF THE THEORY OF ALGORITHMS , 1970 .

[87]  P. Baltes,et al.  Life-Span Developmental Psychology: Research and Theory , 1970 .

[88]  P. Johnson-Laird,et al.  A theoretical analysis of insight into a reasoning task , 1970 .

[89]  J. Horn.  CHAPTER 16 – Organization of Data on Life-Span Development of Human Abilities , 1970 .

[90]  J. Guilford,et al.  The nature of human intelligence. , 1968 .

[91]  R. Bellman.  Dynamic Programming , 1957, Science.

[92]  Ray J. Solomonoff,et al.  A Formal Theory of Inductive Inference. Part II , 1964, Inf. Control..

[93]  E. Boring.  Intelligence as the Tests Test It. , 1961 .

[94]  J. Doob.  Stochastic processes , 1953 .

[95]  J. Piaget.  The Psychology Of Intelligence , 1951 .

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

[97]  L. Thurstone,et al.  Primary mental abilities. , 1938, Science.

[98]  W. V. Bingham.  Aptitudes and aptitude testing , 1937 .

[99]  R. Yerkes,et al.  The Great Apes: A Study of Anthropoid Life , 2017 .

[100]  K. Gödel.  Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I , 1931 .

[101]  C. Spearman.  The Abilities of Man their Nature and Measurement , 2020, Nature.

[102]  A. Binet.  Les Idées modernes sur les enfants , 1910 .