The new AI is general and mathematically rigorous
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[1] Jürgen Schmidhuber,et al. New Millennium AI and the Convergence of History: Update of 2012 , 2012 .
[2] M. Beeson. Foundations of Constructive Mathematics , 1985 .
[3] Martin V. Butz,et al. Anticipatory Behavior in Adaptive Learning Systems , 2003, Lecture Notes in Computer Science.
[4] Jürgen Schmidhuber,et al. Optimal Artificial Curiosity, Creativity, Music, and the Fine Arts , 2005 .
[5] Tao Xiong,et al. A combined SVM and LDA approach for classification , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[6] J. Bell. On the Problem of Hidden Variables in Quantum Mechanics , 1966 .
[7] Jürgen Schmidhuber,et al. Optimal Ordered Problem Solver , 2002, Machine Learning.
[8] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[9] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[10] Jürgen Schmidhuber,et al. Bias-Optimal Incremental Problem Solving , 2002, NIPS.
[11] F. Cajori. A history of mathematics , 1989 .
[12] Nils J. Nilsson,et al. Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] E. Feigenbaum,et al. Computers and Thought , 1963 .
[15] C. Monroe,et al. Experimental entanglement of four particles , 2000, Nature.
[16] Philipp Slusallek,et al. Introduction to real-time ray tracing , 2005, SIGGRAPH Courses.
[17] SolomonoffR.. Complexity-based induction systems , 2006 .
[18] Teuvo Kohonen,et al. Self-Organization and Associative Memory , 1988 .
[19] H. Cantor. Ueber eine Eigenschaft des Inbegriffs aller reellen algebraischen Zahlen. , 1984 .
[20] Jürgen Schmidhuber,et al. A possibility for implementing curiosity and boredom in model-building neural controllers , 1991 .
[21] C. Schmidhuber. Strings from Logic , 2000, hep-th/0011065.
[22] Jürgen Schmidhuber,et al. Artificial Scientists & Artists Based on the Formal Theory of Creativity , 2010, AGI 2010.
[23] Shigeyoshi Tsutsui,et al. Advances in Evolutionary Computing , 2003 .
[24] Jürgen Schmidhuber,et al. Exploring the predictable , 2003 .
[25] Jürgen Schmidhuber,et al. Low-Complexity Art , 2017 .
[26] Jürgen Schmidhuber,et al. Algorithmic Theories of Everything , 2000, ArXiv.
[27] Jürgen Schmidhuber,et al. Gödel Machines: Fully Self-referential Optimal Universal Self-improvers , 2007, Artificial General Intelligence.
[28] Jürgen Schmidhuber,et al. Completely Self-referential Optimal Reinforcement Learners , 2005, ICANN.
[29] Jürgen Schmidhuber. 2006: Celebrating 75 Years of AI - History and Outlook: The Next 25 Years , 2006, 50 Years of Artificial Intelligence.
[30] Gregory J. Chaitin,et al. Algorithmic Information Theory , 1987, IBM J. Res. Dev..
[31] Luca Maria Gambardella,et al. Ant Algorithms for Discrete Optimization , 1999, Artificial Life.
[32] Marcus Hutter. The Fastest and Shortest Algorithm for all Well-Defined Problems , 2002, Int. J. Found. Comput. Sci..
[33] Jürgen Schmidhuber,et al. The New AI: General & Sound & Relevant for Physics , 2003, Artificial General Intelligence.
[34] 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 .
[35] Ray J. Solomonoff,et al. Complexity-based induction systems: Comparisons and convergence theorems , 1978, IEEE Trans. Inf. Theory.
[36] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[37] Ingo Rechenberg,et al. Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .
[38] Jürgen Schmidhuber,et al. A Computer Scientist's View of Life, the Universe, and Everything , 1999, Foundations of Computer Science: Potential - Theory - Cognition.
[39] Andrew P. Sage,et al. Uncertainty in Artificial Intelligence , 1987, IEEE Transactions on Systems, Man, and Cybernetics.
[40] Wilfried Brauer,et al. Foundations of computer science : potential--theory--cognition , 1997 .
[41] Reinhold Behringer,et al. The seeing passenger car 'VaMoRs-P' , 1994, Proceedings of the Intelligent Vehicles '94 Symposium.
[42] Sepp Hochreiter,et al. Learning to Learn Using Gradient Descent , 2001, ICANN.
[43] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[44] Ray J. Solomonoff,et al. The Application of Algorithmic Probability to Problems in Artificial Intelligence , 1985, UAI.
[45] P. Werbos,et al. Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .
[46] K. Gödel. Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I , 1931 .
[47] Jürgen Schmidhuber,et al. Curious model-building control systems , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.
[48] John von Neumann,et al. Theory Of Self Reproducing Automata , 1967 .
[49] A. Kolmogorov. Three approaches to the quantitative definition of information , 1968 .
[50] Michael Barr,et al. The Emperor's New Mind , 1989 .
[51] Jürgen Schmidhuber,et al. Solving POMDPs with Levin Search and EIRA , 1996, ICML.
[52] C. S. Wallace,et al. An Information Measure for Classification , 1968, Comput. J..
[53] L. E. J. Brouwer,et al. Over de Grondslagen der Wiskunde , 2009 .
[54] Jürgen Schmidhuber,et al. Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement , 1997, Machine Learning.
[55] J. Schmidhuber. What''s interesting? , 1997 .
[56] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[57] H. Everett. "Relative State" Formulation of Quantum Mechanics , 1957 .
[58] Jürgen Schmidhuber,et al. An on-line algorithm for dynamic reinforcement learning and planning in reactive environments , 1990, 1990 IJCNN International Joint Conference on Neural Networks.
[59] David P. DiVincenzo,et al. Quantum information and computation , 2000, Nature.
[60] Gregory J. Chaitin,et al. A recent technical report , 1974, SIGA.
[61] Jürgen Schmidhuber,et al. Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity , 2007, Discovery Science.
[62] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[63] Leopold Löwenheim. Über Möglichkeiten im Relativkalkül , 1915 .
[64] A. Turing. On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .
[65] Jürgen Schmidhuber,et al. Hierarchies of Generalized Kolmogorov Complexities and Nonenumerable Universal Measures Computable in the Limit , 2002, Int. J. Found. Comput. Sci..
[66] Konrad Zuse,et al. Rechnender Raum , 1991, Physik und Informatik.
[67] K. Popper,et al. The Logic of Scientific Discovery , 1960 .
[68] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[69] J. Schmidhuber. Don't forget randomness is still just a hypothesis , 2006, Nature.
[70] Ming Li,et al. An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.
[71] Rodney A. Brooks,et al. Intelligence Without Reason , 1991, IJCAI.
[72] T. Erber,et al. Randomness in quantum mechanics—nature's ultimate cryptogram? , 1985, Nature.
[73] Jürgen Schmidhuber,et al. Driven by Compression Progress , 2008, KES.
[74] Fumiya Iida,et al. 50 Years of Artificial Intelligence, Essays Dedicated to the 50th Anniversary of Artificial Intelligence , 2007, 50 Years of Artificial Intelligence.
[75] John E. Laird,et al. The soar papers : research on integrated intelligence , 1993 .
[76] R. Reiter,et al. IJCAI-91: proceedings of the twelfth International Joint Conference on Artificial Intelligence : Darling Harbour, Sydney, Australia, 24-30 august 1991 , 1991 .
[77] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[78] G. Hooft. Quantum gravity as a dissipative deterministic system , 1999, gr-qc/9903084.
[79] Jürgen Schmidhuber,et al. Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes , 2008, ABiALS.
[80] Ray J. Solomonoff,et al. A Formal Theory of Inductive Inference. Part II , 1964, Inf. Control..
[81] Rolf Pfeifer,et al. Understanding intelligence , 2020, Inequality by Design.
[82] T. Toffoli,et al. Conservative logic , 2002, Collision-Based Computing.
[83] Jürgen Schmidhuber,et al. Discovering Neural Nets with Low Kolmogorov Complexity and High Generalization Capability , 1997, Neural Networks.
[84] Jr. Hartley Rogers. Theory of Recursive Functions and Effective Computability , 1969 .
[85] Allen Newell,et al. GPS, a program that simulates human thought , 1995 .
[86] Ray J. Solomonofi,et al. A SYSTEM FOR INCREMENTAL LEARNING BASED ON ALGORITHMIC PROBABILITY , 1989 .
[87] Jürgen Schmidhuber. Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability , 1995, ICML.
[88] Jürgen Schmidhuber,et al. Simple algorithmic theory of subjective beauty, novelty, surprise, interestingness, attention, curiosity, creativity, art, science, music, jokes (特集 高次機能の学習と創発--脳・ロボット・人間研究における新たな展開) , 2009 .
[89] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[90] Hilary Putnam,et al. Trial and error predicates and the solution to a problem of Mostowski , 1965, Journal of Symbolic Logic.
[91] Gregory. J. Chaitin,et al. Algorithmic information theory , 1987, Cambridge tracts in theoretical computer science.
[92] A. Kolmogoroff. Grundbegriffe der Wahrscheinlichkeitsrechnung , 1933 .
[93] Paul E. Utgoff,et al. Shift of bias for inductive concept learning , 1984 .
[94] Neri Merhav,et al. Universal Prediction , 1998, IEEE Trans. Inf. Theory.
[95] W. Vent,et al. Rechenberg, Ingo, Evolutionsstrategie — Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. 170 S. mit 36 Abb. Frommann‐Holzboog‐Verlag. Stuttgart 1973. Broschiert , 1975 .
[96] Jürgen Schmidhuber,et al. Ultimate Cognition à la Gödel , 2009, Cognitive Computation.
[97] Dr. Marcus Hutter,et al. Universal artificial intelligence , 2004 .
[98] Jürgen Schmidhuber,et al. The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions , 2002, COLT.
[99] Péter Gács,et al. On the relation between descriptional complexity and algorithmic probability , 1981, 22nd Annual Symposium on Foundations of Computer Science (sfcs 1981).