{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:39:58Z","timestamp":1760243998142,"version":"build-2065373602"},"reference-count":192,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2009,7,2]],"date-time":"2009-07-02T00:00:00Z","timestamp":1246492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Specialized intelligent systems can be found everywhere: finger print, handwriting, speech, and face recognition, spam filtering, chess and other game programs, robots, et al. This decade the first presumably complete mathematical theory of artificial intelligence based on universal induction-prediction-decision-action has been proposed. This informationtheoretic approach solidifies the foundations of inductive inference and artificial intelligence. Getting the foundations right usually marks a significant progress and maturing of a field. The theory provides a gold standard and guidance for researchers working on intelligent algorithms. The roots of universal induction have been laid exactly half-a-century ago and the roots of universal intelligence exactly one decade ago. So it is timely to take stock of what has been achieved and what remains to be done. Since there are already good recent surveys, I describe the state-of-the-art only in passing and refer the reader to the literature. This article concentrates on the open problems in universal induction and its extension to universal intelligence.<\/jats:p>","DOI":"10.3390\/a2030879","type":"journal-article","created":{"date-parts":[[2009,7,3]],"date-time":"2009-07-03T03:00:00Z","timestamp":1246590000000},"page":"879-906","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Open Problems in Universal Induction &amp; Intelligence"],"prefix":"10.3390","volume":"2","author":[{"given":"Marcus","family":"Hutter","sequence":"first","affiliation":[{"name":"Research School of Information Sciences and Engineering (RSISE), Australian National University, and Statistical Machine Learning (SML), NICTA, Canberra, ACT, 0200, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2009,7,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hume\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t              D.\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t            \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          A Treatise of Human Nature, Book I\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t         [Edited version by L. A. Selby-Bigge and P. H. Nidditch, Oxford University Press, 1978; 1739.","DOI":"10.1093\/oseo\/instance.00046221"},{"key":"ref_2","unstructured":"Popper\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t              K.R.\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t            \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Logik der Forschung\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Springer\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Berlin, Germany\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          1934\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t         [English translation: The Logic of Scientific Discovery Basic Books, New York, NY, USA, 1959, and Hutchinson, London, UK, revised edition, 1968."},{"key":"ref_3","unstructured":"Howson, C. (2003). Hume\u2019s Problem: Induction and the Justification of Belief, Oxford University Press. [2nd Ed.]."},{"key":"ref_4","unstructured":"Levi, I. (1974). Gambling with Truth: An Essay on Induction and the Aims of Science, MIT Press."},{"key":"ref_5","unstructured":"Earman, J. (1993). Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory, MIT Press."},{"key":"ref_6","unstructured":"Wallace, C.S. (2005). Statistical and Inductive Inference by Minimum Message Length, Springer."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Salmon, W.C. (2006). Four Decades of Scientific Explanation, University of Pittsburgh Press.","DOI":"10.2307\/j.ctt5vkdm7"},{"key":"ref_8","unstructured":"Frigg, R., and Hartmann, S. Models in science. http:\/\/plato.stanford.edu\/entries\/models-science\/."},{"key":"ref_9","unstructured":"Wikipedia (2008). Predictive modelling."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Brockwell, P.J., and Davis, R.A. (2002). Introduction to Time Series and Forecasting, Springer. [2nd Ed.].","DOI":"10.1007\/b97391"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Cesa-Bianchi, N., and Lugosi, G. (2006). Prediction, Learning, and Games, Cambridge University Press.","DOI":"10.1017\/CBO9780511546921"},{"key":"ref_12","unstructured":"Geisser, S. (1993). Predictive Inference, Chapman & Hall\/CRC."},{"key":"ref_13","unstructured":"Chatfield, C. (2003). The Analysis of Time Series: An Introduction, Chapman & Hall \/ CRC. [6th Ed.]."},{"key":"ref_14","unstructured":"Ferguson, T.S. (1967). Mathematical Statistics: A Decision Theoretic Approach, Academic Press. [3rd Ed.]."},{"key":"ref_15","unstructured":"DeGroot, M.H. (1970). Optimal Statistical Decisions, McGraw-Hill."},{"key":"ref_16","unstructured":"Jeffrey, R.C. (1983). The Logic of Decision, University of Chicago Press. [2nd Ed.]."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Paris, J.B. (1995). The Uncertain Reasoner\u2019s Companion: A Mathematical Perspective, Cambridge University Press.","DOI":"10.1017\/CBO9780511526596"},{"key":"ref_18","first-page":"971","article-title":"Optimality of universal Bayesian prediction for general loss and alphabet","volume":"4","author":"Hutter","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"ref_19","unstructured":"Hutter, M. (2007). Universal algorithmic intelligence: A mathematical top\u2192down approach, In Artificial General Intelligence, Springer."},{"key":"ref_20","unstructured":"Bertsekas, D.P. (2006). Dynamic Programming and Optimal Control, volume I and II, Athena Scientific. [3rd Ed.]."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1177\/0048393103252780","article-title":"Toward a monistic theory of science: The \u2018strong programme\u2019 reconsidered","volume":"33","author":"Kemp","year":"2003","journal-title":"Philosophy of the Social Sciences"},{"key":"ref_22","unstructured":"Kellert, S.H., Longino, H.E., and Waters, C.K. (2006). Scientific Pluralism, Univ. of Minnesota Press."},{"key":"ref_23","unstructured":"Green, M.B., Schwarz, J.H., and Witten, E. (2000). Superstring Theory: Volumes 1 and 2, Cambridge University Press."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Greene, B. (2000). The Elegant Universe: Superstrings, Hidden Dimensions, and the Quest for the Ultimate Theory, Vintage Press.","DOI":"10.1119\/1.19379"},{"key":"ref_25","unstructured":"Russell, S.J., and Norvig, P. (2003). Artificial Intelligence. A Modern Approach, Prentice-Hall. [2nd Ed.]."},{"key":"ref_26","unstructured":"Hutter, M. A theory of universal artificial intelligence based on algorithmic complexity. http:\/\/arxiv.org\/abs\/cs.AI\/0004001."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Hutter, M. (2005). Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability, Springer. 300 pages, http:\/\/www.hutter1.net\/ai\/uaibook.htm.","DOI":"10.1007\/b138233"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1016\/j.artint.2006.10.005","article-title":"Book review: Marcus Hutter, universal artificial intelligence, Springer (2004)","volume":"170","author":"Oates","year":"2006","journal-title":"Artificial Intelligence"},{"key":"ref_29","unstructured":"Solomonoff\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t              R.J.\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t            \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          A preliminary report on a general theory of inductive inference\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Technical Report V-131\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Zator Co.\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Cambridge, MA, USA\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          1960\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t         Distributed at the Conference on Cerebral Systems and Computers, 8\u201311 Feb. 1960."},{"key":"ref_30","unstructured":"Bellman, R.E. (1957). Dynamic Programming, Princeton University Press."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.tcs.2007.05.016","article-title":"On universal prediction and Bayesian confirmation","volume":"384","author":"Hutter","year":"2007","journal-title":"Theoretical Computer Science"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s11023-007-9079-x","article-title":"Universal intelligence: A definition of machine intelligence","volume":"17","author":"Legg","year":"2007","journal-title":"Minds & Machines"},{"key":"ref_33","unstructured":"Franklin, J. (2002). The Science of Conjecture: Evidence and Probability before Pascal, Johns Hopkins University Press."},{"key":"ref_34","unstructured":"Asmis, E. (1984). Epicurus\u2019 Scientific Method, Cornell Univ. Press."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1112\/plms\/s2-42.1.230","article-title":"On computable numbers, with an application to the Entscheidungsproblem","volume":"2","author":"Turing","year":"1937","journal-title":"Proc. London Mathematical Society"},{"key":"ref_36","first-page":"376","article-title":"An essay towards solving a problem in the doctrine of chances","volume":"53","author":"Bayes","year":"1763","journal-title":"Philosophical Transactions of the Royal Society"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0019-9958(64)90223-2","article-title":"A formal theory of inductive inference: Parts 1 and 2","volume":"7","author":"Solomonoff","year":"1964","journal-title":"Information and Control"},{"key":"ref_38","first-page":"1","article-title":"Three approaches to the quantitative definition of information","volume":"1","author":"Kolmogorov","year":"1965","journal-title":"Problems of Information and Transmission"},{"key":"ref_39","unstructured":"Berger, J. (1993). Statistical Decision Theory and Bayesian Analysis, Springer. [3rd Ed.]."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2519","DOI":"10.4249\/scholarpedia.2519","article-title":"Algorithmic information theory: a brief non-technical guide to the field","volume":"2","author":"Hutter","year":"2007","journal-title":"Scholarpedia"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Li, M., and Vit\u00e1nyi, P.M.B. (2008). An Introduction to Kolmogorov Complexity and its Applications, Springer. [3rd Ed.].","DOI":"10.1007\/978-0-387-49820-1"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2573","DOI":"10.4249\/scholarpedia.2573","article-title":"Algorithmic complexity","volume":"3","author":"Hutter","year":"2008","journal-title":"Scholarpedia"},{"key":"ref_43","unstructured":"MacKay, D.J.C. (2003). Information theory, inference and learning algorithms, Cambridge University Press."},{"key":"ref_44","unstructured":"Cover, T.M., and Thomas, J.A. (2006). Elements of Information Theory, Wiley-Intersience. [2nd Ed.]."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1109\/TIT.1976.1055501","article-title":"On the complexity of finite sequences","volume":"22","author":"Lempel","year":"1976","journal-title":"IEEE Transactions on Information Theory"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1109\/TIT.2005.844059","article-title":"Clustering by compression","volume":"51","author":"Cilibrasi","year":"2005","journal-title":"IEEE Trans. Information Theory"},{"key":"ref_47","unstructured":"Willems, F.M.J., Shtarkov, Y.M., and Tjalkens, T.J. (1997). IEEE Information Theory Society Newsletter."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2572","DOI":"10.4249\/scholarpedia.2572","article-title":"Algorithmic probability","volume":"2","author":"Hutter","year":"2007","journal-title":"Scholarpedia"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1070\/RM1970v025n06ABEH001269","article-title":"The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms","volume":"25","author":"Zvonkin","year":"1970","journal-title":"Russian Mathematical Surveys"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1109\/TIT.1978.1055913","article-title":"Complexity-based induction systems: Comparisons and convergence theorems","volume":"IT-24","author":"Solomonoff","year":"1978","journal-title":"IEEE Transactions on Information Theory"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2658","DOI":"10.4249\/scholarpedia.2658","article-title":"Applications of algorithmic information theory","volume":"2","author":"Li","year":"2007","journal-title":"Scholarpedia"},{"key":"ref_52","unstructured":"Poland, J., and Hutter, M. (,  2006). Universal learning of repeated matrix games. Proc. 15th Annual Machine Learning Conf. of Belgium and The Netherlands (Benelearn\u201906), Ghent, Belgium."},{"key":"ref_53","unstructured":"Pankov, S. (,  2008). A computational approximation to the AIXI model. Proc. 1st Conference on Artificial General Intelligence."},{"key":"ref_54","unstructured":"Hutter, M. (,  2001). Universal sequential decisions in unknown environments. Proc. 5th European Workshop on Reinforcement Learning (EWRL-5), Onderwijsinsituut CKI, Utrecht Univ., Netherlands."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2001). Towards a universal theory of artificial intelligence based on algorithmic probability and sequential decisions. Proc. 12th European Conf. on Machine Learning (ECML\u201901), Freiburg, Germany. LNAI.","DOI":"10.1007\/3-540-44795-4_20"},{"key":"ref_56","unstructured":"Legg, S. (2008). Machine Super Intelligence. [PhD thesis, IDSIA]."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1145\/321356.321363","article-title":"On the length of programs for computing finite binary sequences","volume":"13","author":"Chaitin","year":"1966","journal-title":"Journal of the ACM"},{"key":"ref_58","unstructured":"Neumann, J.V., and Morgenstern, O. (1944). Theory of Games and Economic Behavior, Princeton University Press."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Sutton, R.S., and Barto, A.G. (1998). Reinforcement Learning: An Introduction, MIT Press.","DOI":"10.1109\/TNN.1998.712192"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1016\/S0019-9958(66)80018-9","article-title":"The definition of random sequences","volume":"9","year":"1966","journal-title":"Information and Control"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/S0019-9958(84)80060-1","article-title":"Randomness conservation inequalities: Information and independence in mathematical theories","volume":"61","author":"Levin","year":"1984","journal-title":"Information and Control"},{"key":"ref_62","first-page":"265","article-title":"Universal sequential search problems","volume":"9","author":"Levin","year":"1973","journal-title":"Problems of Information Transmission"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Schmidhuber, J. (,  2002). The speed prior: A new simplicity measure yielding near-optimal computable predictions. Proc. 15th Conf. on Computational Learning Theory (COLT\u201902), Sydney, Australia. LNAI.","DOI":"10.1007\/3-540-45435-7_15"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Chaitin, G.J. (1987). Algorithmic Information Theory, Cambridge University Press.","DOI":"10.1017\/CBO9780511608858"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Chaitin, G.J. (2003). The Limits of Mathematics: A Course on Information Theory and the Limits of Formal Reasoning, Springer.","DOI":"10.1007\/978-1-4471-0015-7"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1142\/S0129054102001291","article-title":"Hierarchies of generalized Kolmogorov complexities and nonenumerable universal measures computable in the limit","volume":"13","author":"Schmidhuber","year":"2002","journal-title":"International Journal of Foundations of Computer Science"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2443","DOI":"10.1109\/18.945257","article-title":"Algorithmic statistics","volume":"47","author":"Tromp","year":"2001","journal-title":"IEEE Transactions on Information Theory"},{"key":"ref_68","unstructured":"Vereshchagin, N., and Vit\u00e1nyi, P.M.B. (,  2002). Kolmogorov\u2019s structure functions with an application to the foundations of model selection. Proc. 43rd Symposium on Foundations of Computer Science, Vancouver, Canada."},{"key":"ref_69","first-page":"588","article-title":"Meaningful information","volume":"2518","year":"2002","journal-title":"Proc. 13th International Symposium on Algorithms and Computation (ISAAC\u201902)"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1093\/comjnl\/11.2.185","article-title":"An information measure for classification","volume":"11","author":"Wallace","year":"1968","journal-title":"Computer Journal"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/0005-1098(78)90005-5","article-title":"Modeling by shortest data description","volume":"14","author":"Rissanen","year":"1978","journal-title":"Automatica"},{"key":"ref_72","unstructured":"Rissanen, J.J. (1989). Stochastic Complexity in Statistical Inquiry, World Scientific."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/0890-5401(89)90010-2","article-title":"Inferring decision trees using the minimum description length principle","volume":"80","author":"Quinlan","year":"1989","journal-title":"Information and Computation"},{"key":"ref_74","unstructured":"Gao, Q., and Li, M. (,  1989). The minimum description length principle and its application to online learning of handprinted characters. Proc. 11th International Joint Conf. on Artificial Intelligence, Detroit, MI, USA."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/BF00993061","article-title":"Discovery by minimal length encoding: A case study in molecular evolution","volume":"12","author":"Jurka","year":"1993","journal-title":"Machine Learning"},{"key":"ref_76","unstructured":"Pednault, E.P.D. (,  1989). Some experiments in applying inductive inference principles to surface reconstruction. Proc. 11th International Joint Conf. on Artificial Intelligence, San Mateo, CA, USA."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Gr\u00fcnwald, P.D. (2007). The Minimum Description Length Principle, The MIT Press.","DOI":"10.7551\/mitpress\/4643.001.0001"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Cilibrasi, R., and Vit\u00e1nyi, P.M.B. (,  2006). Similarity of objects and the meaning of words. Proc. 3rd Annual Conferene on Theory and Applications of Models of Computation (TAMC\u201906), Beijing, China. LNCS.","DOI":"10.1007\/11750321_2"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1016\/S0893-6080(96)00127-X","article-title":"Discovering neural nets with low Kolmogorov complexity and high generalization capability","volume":"10","author":"Schmidhuber","year":"1997","journal-title":"Neural Networks"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1023\/A:1007383707642","article-title":"Shifting inductive bias with success-story algorithm, adaptive Levin search, and incremental self-improvement","volume":"28","author":"Schmidhuber","year":"1997","journal-title":"Machine Learning"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1023\/B:MACH.0000015880.99707.b2","article-title":"Optimal ordered problem solver","volume":"54","author":"Schmidhuber","year":"2004","journal-title":"Machine Learning"},{"key":"ref_82","first-page":"97","article-title":"Low-complexity art","volume":"30","author":"Schmidhuber","year":"1997","journal-title":"Leonardo, Journal of the International Society for the Arts, Sciences, and Technology"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Calude, C.S. (2002). Information and Randomness: An Algorithmic Perspective, Springer. [2nd Ed.].","DOI":"10.1007\/978-3-662-04978-5"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1142\/S0129054102001199","article-title":"The fastest and shortest algorithm for all well-defined problems","volume":"13","author":"Hutter","year":"2002","journal-title":"International Journal of Foundations of Computer Science"},{"key":"ref_85","unstructured":"Stork, D. Foundations of Occam\u2019s razor and parsimony in learning. http:\/\/www.rii.ricoh.com\/\u223cstork\/OccamWorkshop.html."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2003). On the existence and convergence of computable universal priors. Proc. 14th International Conf. on Algorithmic Learning Theory (ALT\u201903), Sapporo, Japan. LNAI.","DOI":"10.1007\/978-3-540-39624-6_24"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.tcs.2006.07.039","article-title":"On generalized computable universal priors and their convergence","volume":"364","author":"Hutter","year":"2006","journal-title":"Theoretical Computer Science"},{"key":"ref_88","first-page":"239","article-title":"Convergence and error bounds for universal prediction of nonbinary sequences","volume":"Vol. 2167","author":"Hutter","year":"2001","journal-title":"Proc. 12th European Conf. on Machine Learning (ECML\u201901)"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1006\/jcss.2000.1743","article-title":"New error bounds for Solomonoff prediction","volume":"62","author":"Hutter","year":"2001","journal-title":"Journal of Computer and System Sciences"},{"key":"ref_90","unstructured":"Hutter, M. (,  2001). General loss bounds for universal sequence prediction. Proc. 18th International Conf. on Machine Learning (ICML\u201901), Williams College, Williamstown, MA, USA."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2061","DOI":"10.1109\/TIT.2003.814488","article-title":"Convergence and loss bounds for Bayesian sequence prediction","volume":"49","author":"Hutter","year":"2003","journal-title":"IEEE Transactions on Information Theory"},{"key":"ref_92","unstructured":"Hutter, M. Online prediction \u2013 Bayes versus experts. Technical report, http:\/\/www.hutter1.net\/ai\/bayespea.htm."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Chernov, A., and Hutter, M. (,  2005). Monotone conditional complexity bounds on future prediction errors. Proc. 16th International Conf. on Algorithmic Learning Theory (ALT\u201905), Singapore. LNAI.","DOI":"10.1007\/11564089_32"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.ic.2006.10.004","article-title":"Algorithmic complexity bounds on future prediction errors","volume":"205","author":"Chernov","year":"2007","journal-title":"Information and Computation"},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2003). Sequence prediction based on monotone complexity. Proc. 16th Annual Conf. on Learning Theory (COLT\u201903), Washington, DC, USA. LNAI.","DOI":"10.1007\/978-3-540-45167-9_37"},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jcss.2005.07.001","article-title":"Sequential predictions based on algorithmic complexity","volume":"72","author":"Hutter","year":"2006","journal-title":"Journal of Computer and System Sciences"},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Poland, J., and Hutter, M. (,  2004). Convergence of discrete MDL for sequential prediction. Proc. 17th Annual Conf. on Learning Theory (COLT\u201904), Banff, Canada. LNAI.","DOI":"10.1007\/978-3-540-27819-1_21"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"3780","DOI":"10.1109\/TIT.2005.856956","article-title":"Asymptotics of discrete MDL for online prediction","volume":"51","author":"Poland","year":"2005","journal-title":"IEEE Transactions on Information Theory"},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Poland, J., and Hutter, M. (,  2004). On the convergence speed of MDL predictions for Bernoulli sequences. Proc. 15th International Conf. on Algorithmic Learning Theory (ALT\u201904), Padova, Italy. LNAI.","DOI":"10.1007\/978-3-540-30215-5_23"},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s11222-006-6746-3","article-title":"MDL convergence speed for Bernoulli sequences","volume":"16","author":"Poland","year":"2006","journal-title":"Statistics and Computing"},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2003). An open problem regarding the convergence of universal a priori probability. Proc. 16th Annual Conf. on Learning Theory (COLT\u201903), Washington, DC, USA. LNAI.","DOI":"10.1007\/978-3-540-45167-9_58"},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Hutter, M., and Muchnik, A.A. (,  2004). Universal convergence of semimeasures on individual random sequences. Proc. 15th International Conf. on Algorithmic Learning Theory (ALT\u201904), Padova, Italy. LNAI.","DOI":"10.1007\/978-3-540-30215-5_19"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.tcs.2007.03.040","article-title":"On semimeasures predicting Martin-L\u00f6f random sequences","volume":"382","author":"Hutter","year":"2007","journal-title":"Theoretical Computer Science"},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2006). On the foundations of universal sequence prediction. Proc. 3rd Annual Conference on Theory and Applications of Models of Computation (TAMC\u201906), Beijing, China. LNCS.","DOI":"10.1007\/11750321_39"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Michie, D. (1966). Game-playing and game-learning automata, In Advances in Programming and Non-Numerical Computation, Pergamon.","DOI":"10.1016\/B978-0-08-011356-2.50011-2"},{"key":"ref_106","doi-asserted-by":"crossref","unstructured":"Berry, D.A., and Fristedt, B. (1985). Bandit Problems: Sequential Allocation of Experiments, Chapman and Hall.","DOI":"10.1007\/978-94-015-3711-7"},{"key":"ref_107","unstructured":"Duff, M. (2002). Optimal Learning: Computational procedures for Bayes-adaptive Markov decision processes. [PhD thesis, Department of Computer Science, University of Massachusetts Amherst]."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Szita, I., and L\u00f6rincz, A. (,  2008). The many faces of optimism: a unifying approach. Proc. 12th International Conference (ICML 2008).","DOI":"10.1145\/1390156.1390288"},{"key":"ref_109","unstructured":"Kumar, P.R., and Varaiya, P.P. (1986). Stochastic Systems: Estimation, Identification, and Adaptive Control, Prentice Hall."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1109\/9.16415","article-title":"Asymptotically efficient adaptive allocation schemes for controlled i.i.d. processes: Finite parameter space","volume":"34","author":"Agrawal","year":"1989","journal-title":"IEEE Trans. Automatic Control"},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1109\/9.40770","article-title":"Asymptotically efficient adaptive allocation schemes for controlled Markov chains: Finite parameter space","volume":"34","author":"Agrawal","year":"1989","journal-title":"IEEE Trans. Automatic Control"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1147\/rd.33.0210","article-title":"Some studies in machine learning using the game of checkers","volume":"3","author":"Samuel","year":"1959","journal-title":"IBM Journal on Research and Development"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TSMC.1983.6313077","article-title":"Neuronlike adaptive elements that can solve difficult learning control problems","volume":"834","author":"Barto","year":"1983","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics"},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1007\/BF00115009","article-title":"Learning to predict by the methods of temporal differences","volume":"3","author":"Sutton","year":"1988","journal-title":"Machine Learning"},{"key":"ref_115","unstructured":"Watkins, C. (1989). Learning from Delayed Rewards. [PhD thesis, King\u2019s College]."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF00992698","article-title":"Q-learning","volume":"8","author":"Watkins","year":"1992","journal-title":"Machine Learning"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/BF00993104","article-title":"Prioritized sweeping: Reinforcement learning with less data and less time","volume":"13","author":"Moore","year":"1993","journal-title":"Machine Learning"},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1162\/neco.1994.6.2.215","article-title":"\u201cTD\u201d-Gammon, a self-teaching backgammon program, achieves master-level play","volume":"6","author":"Tesauro","year":"1994","journal-title":"Neural Computation"},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1023\/A:1007562800292","article-title":"Fast online \u201cQ\u201d(\u03bb)","volume":"33","author":"Wiering","year":"1998","journal-title":"Machine Learning"},{"key":"ref_120","unstructured":"Kearns, M., and Koller, D. (,  1999). Efficient reinforcement learning in factored MDPs. Proc. 16th International Joint Conference on Artificial Intelligence (IJCAI-99), Stockholm, Sweden."},{"key":"ref_121","first-page":"77","article-title":"Reinforcement learning soccer teams with incomplete world models","volume":"7","author":"Wiering","year":"1999","journal-title":"Artificial Neural Networks for Robot Learning. Special issue of Autonomous Robots"},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1023\/A:1007593124513","article-title":"Toward a model of intelligence as an economy of agents","volume":"35","author":"Baum","year":"1999","journal-title":"Machine Learning"},{"key":"ref_123","unstructured":"Koller, D., and Parr, R. (,  2000). Policy iteration for factored MDPs. Proc. 16th Conference on Uncertainty in Artificial Intelligence (UAI-00), Stanford University, Stanford, CA, USA."},{"key":"ref_124","unstructured":"Singh, S., Littman, M., Jong, N., Pardoe, D., and Stone, P. (,  2003). Learning predictive state representations. Proc. 20th International Conference on Machine Learning (ICML\u201903), Washington, DC, USA."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1613\/jair.1000","article-title":"Efficient solution algorithms for factored MDPs","volume":"19","author":"Guestrin","year":"2003","journal-title":"Journal of Artificial Intelligence Research (JAIR)"},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.tcs.2008.06.039","article-title":"On the possibility of learning in reactive environments with arbitrary dependence","volume":"405","author":"Ryabko","year":"2008","journal-title":"Theoretical Computer Science"},{"key":"ref_127","unstructured":"Strehl, A.L., Diuk, C., and Littman, M.L. (,  2007). Efficient structure learning in factored-state MDPs. Proc. 27th AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1613\/jair.2567","article-title":"Online planning algorithms for POMDPs","volume":"2008","author":"Ross","year":"2008","journal-title":"Journal of Artificial Intelligence Research"},{"key":"ref_129","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2009). Feature Markov decision processes. Proc. 2nd Conf. on Artificial General Intelligence (AGI\u201909), Arlington, VA, USA.","DOI":"10.2991\/agi.2009.30"},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2009). Feature dynamic Bayesian networks. Proc. 2nd Conf. on Artificial General Intelligence (AGI\u201909), Arlington, VA, USA.","DOI":"10.2991\/agi.2009.6"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1613\/jair.301","article-title":"Reinforcement learning: a survey","volume":"4","author":"Kaelbling","year":"1996","journal-title":"Journal of Artificial Intelligence Research"},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/S0004-3702(98)00023-X","article-title":"Planning and acting in partially observable stochastic domains","volume":"101","author":"Kaelbling","year":"1998","journal-title":"Artificial Intelligence"},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1613\/jair.575","article-title":"Decision-theoretic planning: Structural assumptions and computational leverage","volume":"11","author":"Boutilier","year":"1999","journal-title":"Journal of Artificial Intelligence Research"},{"key":"ref_134","first-page":"363","article-title":"Autonomous inverted helicopter flight via reinforcement learning","volume":"Vol. 21","author":"Ng","year":"2004","journal-title":"ISER"},{"key":"ref_135","unstructured":"Bertsekas, D.P., and Tsitsiklis, J.N. (1996). Neuro-Dynamic Programming, Athena Scientific."},{"key":"ref_136","unstructured":"Hutter, M. (2004). Bayes optimal agents in general environments, unpublished manuscript."},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2002). Self-optimizing and Pareto-optimal policies in general environments based on Bayes-mixtures. Proc. 15th Annual Conf. on Computational Learning Theory (COLT\u201902), Sydney, Australia. LNAI.","DOI":"10.1007\/3-540-45435-7_25"},{"key":"ref_138","unstructured":"Legg, S., and Hutter, M. (2004). Ergodic MDPs admit self-optimising policies, Technical Report IDSIA-21-04, IDSIA."},{"key":"ref_139","unstructured":"Legg, S., and Hutter, M. (2004). A taxonomy for abstract environments, Technical Report IDSIA-20-04, IDSIA."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"2575","DOI":"10.4249\/scholarpedia.2575","article-title":"Universal search","volume":"2","author":"Gaglio","year":"2007","journal-title":"Scholarpedia"},{"key":"ref_141","unstructured":"Schmidhuber, J. G\u00f6del machines: Self-referential universal problem solvers making provably optimal self-improvements. Artificial General Intelligence, in press."},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Jaynes, E.T. (2003). Probability Theory: The Logic of Science, Cambridge University Press.","DOI":"10.1017\/CBO9780511790423"},{"key":"ref_143","unstructured":"Hitchcock, C. (2004). Contemporary Debates in Philosophy of Science, Blackwell Publishing. chapter 3."},{"key":"ref_144","unstructured":"Rescher, N. (2001). Paradoxes: Their Roots, Range, and Resolution, Open Court."},{"key":"ref_145","unstructured":"Goodman, N. (1983). Fact, Fiction, and Forecast, Harvard University Press. [4th Ed.]."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1080\/01621459.1996.10477003","article-title":"The selection of prior distributions by formal rules","volume":"91","author":"Kass","year":"1996","journal-title":"Journal of the American Statistical Association"},{"key":"ref_147","first-page":"453","article-title":"An invariant form for the prior probability in estimation problems","volume":"Vol. Series A 186","author":"Jeffreys","year":"1946","journal-title":"Proc. Royal Society London"},{"key":"ref_148","unstructured":"Glymour, C. (1980). Theory and Evidence, Princeton Univ. Press."},{"key":"ref_149","unstructured":"Carnap, R. (1952). The Continuum of Inductive Methods, University of Chicago Press."},{"key":"ref_150","unstructured":"Laplace\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t              P.\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t            \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          \n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Th\u00e9orie analytique des probabilit\u00e9s\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          Courcier, Paris, France\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t          1812\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t         [English translation by Truscott, F.W. and Emory, F.L.: A Philosophical Essay on Probabilities. Dover, 1952]."},{"key":"ref_151","doi-asserted-by":"crossref","unstructured":"Press, S.J. (2002). Subjective and Objective Bayesian Statistics: Principles, Models, and Applications, Wiley. [2nd Ed.].","DOI":"10.1002\/9780470317105"},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1214\/06-BA116","article-title":"Subjective bayesian analysis: Principles and practice","volume":"1","author":"Goldstein","year":"2006","journal-title":"Bayesian Analysis"},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/S0304-3975(01)00028-7","article-title":"Kolmogorov entropy in the context of computability theory","volume":"271","author":"Muchnik","year":"2002","journal-title":"Theoretical Computer Science"},{"key":"ref_154","unstructured":"M\u00fcller, M. Stationary algorithmic probability. Technical Report http:\/\/arXiv.org\/abs\/cs\/0608095."},{"key":"ref_155","unstructured":"Ryabko, D., and Hutter, M. (2007). Proc. IEEE International Symposium on Information Theory (ISIT\u201907), IEEE."},{"key":"ref_156","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/j.aml.2007.04.004","article-title":"Predicting non-stationary processes","volume":"21","author":"Ryabko","year":"2008","journal-title":"Applied Mathematics Letters"},{"key":"ref_157","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/S0019-9958(67)91165-5","article-title":"Language identification in the limit","volume":"10","author":"Gold","year":"1967","journal-title":"Information and Control"},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.2307\/2951492","article-title":"Rational learning leads to Nash equilibrium","volume":"61","author":"Kalai","year":"1993","journal-title":"Econometrica"},{"key":"ref_159","unstructured":"Weiss, G. (2000). Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press."},{"key":"ref_160","unstructured":"Littlestone, N., and Warmuth, M.K. (1989). 30th Annual Symposium on Foundations of Computer Science, IEEE."},{"key":"ref_161","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/0890-5401(92)90050-P","article-title":"Universal forecasting algorithms","volume":"96","author":"Vovk","year":"1992","journal-title":"Information and Computation"},{"key":"ref_162","doi-asserted-by":"crossref","unstructured":"Poland, J., and Hutter, M. (,  2005). Defensive universal learning with experts. Proc. 16th International Conf. on Algorithmic Learning Theory (ALT\u201905), Singapore. LNAI.","DOI":"10.1007\/11564089_28"},{"key":"ref_163","doi-asserted-by":"crossref","unstructured":"Ryabko, D., and Hutter, M. (,  2006). Asymptotic learnability of reinforcement problems with arbitrary dependence. Proc. 17th International Conf. on Algorithmic Learning Theory (ALT\u201906), Barcelona, Spain. LNAI.","DOI":"10.1007\/11894841_27"},{"key":"ref_164","doi-asserted-by":"crossref","unstructured":"Hutter, M. (,  2006). General discounting versus average reward. Proc. 17th International Conf. on Algorithmic Learning Theory (ALT\u201906), Barcelona, Spain. LNAI.","DOI":"10.1007\/11894841_21"},{"key":"ref_165","first-page":"17","article-title":"A collection of definitions of intelligence","volume":"Vol. 157","author":"Goertzel","year":"2007","journal-title":"Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms"},{"key":"ref_166","doi-asserted-by":"crossref","unstructured":"Legg, S., and Hutter, M. (,  2007). Tests of machine intelligence. 50 Years of Artificial Intelligence, Monte Verita, Switzerland. LNAI.","DOI":"10.1007\/978-3-540-77296-5_22"},{"key":"ref_167","doi-asserted-by":"crossref","unstructured":"Turing, A.M. (1950). Computing machinery and intelligence. Mind.","DOI":"10.1093\/mind\/LIX.236.433"},{"key":"ref_168","unstructured":"Saygin, A., Cicekli, I., and Akman, V. (2000). Turing test: 50 years later. Minds and Machines, 10."},{"key":"ref_169","unstructured":"Loebner, H. The loebner prize \u2013 the first turing test. http:\/\/www.loebner.net\/Prizef\/loebner-prize.html."},{"key":"ref_170","first-page":"887","article-title":"What is artificial intelligence? psychometric ai as an answer","volume":"18","author":"Bringsjord","year":"2003","journal-title":"Proc. 18th International Joint Conf. on Artificial Intelligence"},{"key":"ref_171","unstructured":"Alvarado, N., Adams, S., Burbeck, S., and Latta, C. (2002). Performance Metrics for Intelligent Systems Workshop."},{"key":"ref_172","unstructured":"Horst, J. (2002). Performance Metrics for Intelligent Systems Workshop."},{"key":"ref_173","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1007\/BF02084159","article-title":"G\u00f6del\u2019s theorem and information","volume":"22","author":"Chaitin","year":"1982","journal-title":"International Journal of Theoretical Physics"},{"key":"ref_174","unstructured":"Hern\u00e1ndez-Orallo, J., and Minaya-Collado, N. (1998). International Symposium of Engineering of Intelligent Systems."},{"key":"ref_175","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1023\/A:1008367325700","article-title":"Beyond the turing test","volume":"9","year":"2000","journal-title":"Journal of Logic, Language and Information"},{"key":"ref_176","unstructured":"Hern\u00e1ndez-Orallo, J. (2000). Performance Metrics for Intelligent Systems Workshop."},{"key":"ref_177","unstructured":"Sanghi, P., and Dowe, D.L. (,  2003). A computer program capable of passing i.q. tests. Proc. 4th ICCS International Conf. on Cognitive Science (ICCS\u201903), Sydney, NSW, Australia."},{"key":"ref_178","unstructured":"Legg, S., and Hutter, M. (,  2006). A formal measure of machine intelligence. Proc. 15th Annual Machine Learning Conference of Belgium and The Netherlands (Benelearn\u201906), Ghent, Belgium."},{"key":"ref_179","doi-asserted-by":"crossref","unstructured":"Graham-Rowe, D. Spotting the bots with brains, New Scientist magazine, (13 August 2005).","DOI":"10.1016\/S0262-4079(06)61303-1"},{"key":"ref_180","first-page":"42","article-title":"Mesurer l\u2019intelligence d\u2019une machine","volume":"Vol. 1","year":"2005","journal-title":"Le Monde de l\u2019intelligence"},{"key":"ref_181","unstructured":"Solso, R.L., MacLin, O.H., and MacLin, M.K. (2007). Cognitive Psychology, Allyn & Bacon. [8th Ed.]."},{"key":"ref_182","unstructured":"Chalmers, D.J. (2002). Philosophy of Mind: Classical and Contemporary Readings, Oxford University Press."},{"key":"ref_183","doi-asserted-by":"crossref","unstructured":"Searle, J.R. (2005). Mind: A Brief Introduction, Oxford University Press.","DOI":"10.1093\/oso\/9780195157338.001.0001"},{"key":"ref_184","unstructured":"Hawkins, J., and Blakeslee, S. (2004). On Intelligence, Times Books."},{"key":"ref_185","unstructured":"Hausser, R. (2001). Foundations of Computational Linguistics: Human-Computer Communication in Natural Language, Springer. [2nd Ed.]."},{"key":"ref_186","doi-asserted-by":"crossref","unstructured":"Chomsky, N. (2006). Language and Mind, Cambridge University Press. [3rd Ed.].","DOI":"10.1017\/CBO9780511791222"},{"key":"ref_187","unstructured":"Park, M.A. (2007). Introducing Anthropology: An Integrated Approach, McGraw-Hill. [4th Ed.]."},{"key":"ref_188","unstructured":"Bishop, C.M. (2006). Pattern Recognition and Machine Learning, Springer."},{"key":"ref_189","unstructured":"Turner, R. (Logics for Artificial Intelligence, 1984). Logics for Artificial Intelligence, Ellis Horwood Series in Artificial Intelligence."},{"key":"ref_190","doi-asserted-by":"crossref","unstructured":"Lloyd, J.W. (1987). Foundations of Logic Programming, Springer. [2nd Ed.].","DOI":"10.1007\/978-3-642-83189-8"},{"key":"ref_191","doi-asserted-by":"crossref","unstructured":"Tettamanzi, A., Tomassini, M., and Jans\u030esen, J. (2001). Soft Computing: Integrating Evolutionary, Neural, and Fuzzy Systems, Springer.","DOI":"10.1007\/978-3-662-04335-6"},{"key":"ref_192","unstructured":"Kardong, K.V. (2007). An Introduction to Biological Evolution, McGraw-Hill Science\/Engineering\/Math. [2nd Ed.]."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/2\/3\/879\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T22:10:40Z","timestamp":1760220640000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/2\/3\/879"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,7,2]]},"references-count":192,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2009,9]]}},"alternative-id":["a2030879"],"URL":"https:\/\/doi.org\/10.3390\/a2030879","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2009,7,2]]}}}