Computational Intelligence: An Introduction

The Artificial Intelligence field continues to be plagued by what can only be described as ‘bold promises for the future syndrome’, often perpetrated by researchers who should know better. While impartial assessment can point to concrete contributions over the past 50 years (such as automated theorem proving, games strategies, the LISP and Prolog high-level computer languages, Automatic Speech Recognition, Natural Language Processing, mobile robot path planning, unmanned vehicles, humanoid robots, data mining, and more), the more cynical argue that AI has witnessed more than its fair share of ‘unmitigated disasters’ during this time – see, for example [3,58,107,125,186]. The general public becomes rapidly jaded with such ‘bold predictions’ that fail to live up to their original hype, and which ultimately render the zealots’ promises as counter-productive.

[1]  A. Bennett The Origin of Species by means of Natural Selection; or the Preservation of Favoured Races in the Struggle for Life , 1872, Nature.

[2]  H. Schubert Grundlagen der Arithmetik , 1898 .

[3]  E. Thorndike On the Organization of Intellect. , 1921 .

[4]  M. Black Vagueness. An Exercise in Logical Analysis , 1937, Philosophy of Science.

[5]  V. Liempt,et al.  Ein Wechselstrom-Coulometer , 1943 .

[6]  Alex Fraser,et al.  Simulation of Genetic Systems by Automatic Digital Computers I. Introduction , 1957 .

[7]  Richard M. Friedberg,et al.  A Learning Machine: Part I , 1958, IBM J. Res. Dev..

[8]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[9]  J. S. F. Barker,et al.  Simulation of Genetic Systems by Automatic Digital Computers , 1958 .

[10]  Richard M. Friedberg,et al.  A Learning Machine: Part II , 1959, IBM J. Res. Dev..

[11]  L. Penrose,et al.  Self-Reproducing Machines , 1959 .

[12]  Arthur L. Samuel,et al.  Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..

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

[14]  A. A. Mullin,et al.  Principles of neurodynamics , 1962 .

[15]  I. S. Gradshtein,et al.  THE ELEMENTS OF MATHEMATICAL LOGIC , 1963 .

[16]  Frank Rosenblatt,et al.  PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS , 1963 .

[17]  Olgierd Wojtasiewicz,et al.  Elements of mathematical logic , 1964 .

[18]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

[19]  John Daniel. Bagley,et al.  The behavior of adaptive systems which employ genetic and correlation algorithms : technical report , 1967 .

[20]  Arthur E. Bryson,et al.  Applied Optimal Control , 1969 .

[21]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[22]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[23]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[24]  P. Werbos,et al.  Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .

[25]  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 .

[26]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

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

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

[29]  Sandy Lovie How the mind works , 1980, Nature.

[30]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[31]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[32]  Z. Pawlak Classification of objects by means of attributes , 1981 .

[33]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[34]  J. D. Schaffer,et al.  Some experiments in machine learning using vector evaluated genetic algorithms (artificial intelligence, optimization, adaptation, pattern recognition) , 1984 .

[35]  C. Langton Self-reproduction in cellular automata , 1984 .

[36]  Zdzislaw Pawlak,et al.  Rough classification , 1984, Int. J. Hum. Comput. Stud..

[37]  Z. Pawlak Principles of knowledge representation , 1984 .

[38]  Mw Hirsch,et al.  Chaos In Dynamical Systems , 2016 .

[39]  Jim Holder,et al.  User interfaces , 1985, ALET.

[40]  Ewa Orlowska,et al.  Semantics of Vague Concepts , 1985 .

[41]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[42]  Chuck Williams,et al.  Expert Systems, Knowledge Engineering, and AI Tools-An Overview , 1986, IEEE Expert.

[43]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[44]  Alan S. Perelson,et al.  The immune system, adaptation, and machine learning , 1986 .

[45]  Peter Jackson,et al.  Introduction to expert systems , 1986 .

[46]  Hubert L. Dreyfus,et al.  Why Expert Systems Do Not Exhibit Expertise , 1986, IEEE Expert.

[47]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[48]  Tommaso Toffoli,et al.  Cellular automata machines - a new environment for modeling , 1987, MIT Press series in scientific computation.

[49]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[50]  S. Grossberg,et al.  ART 2: self-organization of stable category recognition codes for analog input patterns. , 1987, Applied optics.

[51]  Tommaso Toffoli,et al.  Cellular Automata Machines , 1987, Complex Syst..

[52]  Stephen Grossberg,et al.  A massively parallel architecture for a self-organizing neural pattern recognition machine , 1988, Comput. Vis. Graph. Image Process..

[53]  M. J. D. Powell,et al.  Radial basis functions for multivariable interpolation: a review , 1987 .

[54]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[55]  James A. Anderson,et al.  Neurocomputing: Foundations of Research , 1988 .

[56]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[57]  S. Y. Kung,et al.  Parallel architectures for artificial neural nets , 1988, IEEE 1988 International Conference on Neural Networks.

[58]  Robert A. Jacobs,et al.  Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.

[59]  Stephen Grossberg,et al.  Art 2: Self-Organization Of Stable Category Recognition Codes For Analog Input Patterns , 1988, Other Conferences.

[60]  Daniel J. Amit,et al.  Hardware Implementations of Neural Networks , 1989 .

[61]  Carver Mead,et al.  Analog VLSI and neural systems , 1989 .

[62]  Jean,et al.  The Computer and the Brain , 1989, Annals of the History of Computing.

[63]  Vice President,et al.  An Introduction to Expert Systems , 1989 .

[64]  Geoffrey E. Hinton,et al.  Parallel Models of Associative Memory , 1989 .

[65]  Witold Pedrycz,et al.  Fuzzy control and fuzzy systems , 1989 .

[66]  M Conrad,et al.  The brain-machine disanalogy. , 1989, Bio Systems.

[67]  Yann LeCun,et al.  Optimal Brain Damage , 1989, NIPS.

[68]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[69]  Geoffrey E. Hinton,et al.  Evaluation of Adaptive Mixtures of Competing Experts , 1990, NIPS.

[70]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[71]  Thomas Jackson,et al.  Neural Computing - An Introduction , 1990 .

[72]  Tom Tollenaere,et al.  SuperSAB: Fast adaptive back propagation with good scaling properties , 1990, Neural Networks.

[73]  Joseph Williams When expert systems are wrong , 1990, SIGBDP '90.

[74]  Kenneth Falconer,et al.  Fractal Geometry: Mathematical Foundations and Applications , 1990 .

[75]  J. Stephen Judd,et al.  Neural network design and the complexity of learning , 1990, Neural network modeling and connectionism.

[76]  W. Pinebrook The evolution of strategy. , 1990, Case studies in health administration.

[77]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[78]  Naoki Hara,et al.  Fuzzy rule extraction from a multilayered neural network , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[79]  Chyck Karr,et al.  Applying genetics to fuzzy logic , 1991 .

[80]  Richard Reviewer-Granger Unified Theories of Cognition , 1991, Journal of Cognitive Neuroscience.

[81]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[82]  Peter J. F. Lucas,et al.  Principles of expert systems , 1991, International computer science series.

[83]  R. A. Brooks,et al.  Intelligence without Representation , 1991, Artif. Intell..

[84]  Chin-Teng Lin,et al.  Neural-Network-Based Fuzzy Logic Control and Decision System , 1991, IEEE Trans. Computers.

[85]  David M. Skapura,et al.  Neural networks - algorithms, applications, and programming techniques , 1991, Computation and neural systems series.

[86]  Geoffrey E. Hinton,et al.  Adaptive Mixtures of Local Experts , 1991, Neural Computation.

[87]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[88]  Rodney A. Brooks,et al.  Intelligence Without Reason , 1991, IJCAI.

[89]  Martin A. Riedmiller,et al.  RPROP - A Fast Adaptive Learning Algorithm , 1992 .

[90]  James C. Bezdek,et al.  On the relationship between neural networks, pattern recognition and intelligence , 1992, Int. J. Approx. Reason..

[91]  Patrick K. Simpson,et al.  Fuzzy min-max neural networks. I. Classification , 1992, IEEE Trans. Neural Networks.

[92]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[93]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[94]  Gerald Tesauro,et al.  Temporal Difference Learning of Backgammon Strategy , 1992, ML Workshop.

[95]  Ronald R. Yager,et al.  Implementing fuzzy logic controllers using a neural network framework , 1992 .

[96]  Harris Drucker,et al.  Improving Performance in Neural Networks Using a Boosting Algorithm , 1992, NIPS.

[97]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[98]  Stephen D. Collins Neurocomputing 2 , 1992, Neurology.

[99]  Ralph Stair,et al.  Principles of information systems , 2014 .

[100]  P. K. Simpson Fuzzy Min-Max Neural Networks-Part 1 : Classification , 1992 .

[101]  Adam Krzyżak,et al.  Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..

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

[103]  Steven Levy,et al.  Artificial Life: A Report from the Frontier Where Computers Meet Biology , 1993 .

[104]  Yuzo Hirai,et al.  Hardware implementation of neural networks in Japan , 1993, Neurocomputing.

[105]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[106]  Patrick K. Simpson,et al.  Fuzzy min-max neural networks - Part 2: Clustering , 1993, IEEE Trans. Fuzzy Syst..

[107]  H. Takagi,et al.  Integrating Design Stages of Fuzzy Systems using Genetic Algorithms 1 , 1993 .

[108]  Witold Pedrycz,et al.  Fuzzy neural networks and neurocomputations , 1993 .

[109]  M.A. Lee,et al.  Integrating design stage of fuzzy systems using genetic algorithms , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[110]  Allan Pinkus,et al.  Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function , 1991, Neural Networks.

[111]  Gregory J. Wolff,et al.  Optimal Brain Surgeon and general network pruning , 1993, IEEE International Conference on Neural Networks.

[112]  Wojciech Ziarko,et al.  Variable Precision Rough Set Model , 1993, J. Comput. Syst. Sci..

[113]  Naleih M. Botros,et al.  Hardware implementation of an artificial neural network using field programmable gate arrays (FPGA's) , 1994, IEEE Trans. Ind. Electron..

[114]  Y. Uchikawa,et al.  A New Approach to Genetic Based Machine Learning and an Efficient Finding of Fuzzy Rules - Proposal of Nagoya Approach - , 1994, IEEE/Nagoya-University World Wisepersons Workshop.

[115]  George Karypis,et al.  Introduction to Parallel Computing , 1994 .

[116]  Una-May O'Reilly,et al.  Genetic Programming II: Automatic Discovery of Reusable Programs. , 1994, Artificial Life.

[117]  Richard J. Mammone,et al.  Artificial neural networks for speech and vision , 1994 .

[118]  Harris Drucker,et al.  Boosting and Other Ensemble Methods , 1994, Neural Computation.

[119]  Hitoshi Iba,et al.  Evolvable hardware , 1994 .

[120]  Michael I. Jordan,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.

[121]  James C. Bezdek,et al.  Optimization of fuzzy clustering criteria using genetic algorithms , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[122]  Roberto Battiti,et al.  Democracy in neural nets: Voting schemes for classification , 1994, Neural Networks.

[123]  Frank Klawonn,et al.  Foundations of fuzzy systems , 1994 .

[124]  F. Martin McNeill,et al.  Fuzzy Logic: A Practical Approach , 1994 .

[125]  Jacek M. Zurada,et al.  Computational Intelligence: Imitating Life , 1994 .

[126]  Paul J. Werbos,et al.  The Roots of Backpropagation: From Ordered Derivatives to Neural Networks and Political Forecasting , 1994 .

[127]  John Durkin,et al.  Expert systems - design and development , 1994 .

[128]  Earl Cox,et al.  The fuzzy systems handbook , 1994 .

[129]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[130]  Lotfi A. Zadeh,et al.  Fuzzy logic, neural networks, and soft computing , 1993, CACM.

[131]  Ching Y. Suen,et al.  Optimal combinations of pattern classifiers , 1995, Pattern Recognition Letters.

[132]  Lance D. Chambers Practical handbook of genetic algorithms , 1995 .

[133]  Hao Ying,et al.  Essentials of fuzzy modeling and control , 1995 .

[134]  Sung-Bae Cho,et al.  Combining multiple neural networks by fuzzy integral for robust classification , 1995, IEEE Trans. Syst. Man Cybern..

[135]  Mircea Gh. Negoita,et al.  A genetic-based method for learning the parameters of a fuzzy inference system , 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[136]  C. V. Altrock Fuzzy logic and neurofuzzy applications explained , 1995 .

[137]  Sung-Bae Cho,et al.  Multiple network fusion using fuzzy logic , 1995, IEEE Trans. Neural Networks.

[138]  T. Fukuda,et al.  Self-tuning fuzzy modeling with adaptive membership function, rules, and hierarchical structure based on genetic algorithm , 1995 .

[139]  David B. Fogel,et al.  Evolutionary Computation: Towards a New Philosophy of Machine Intelligence , 1995 .

[140]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[141]  Francisco Herrera,et al.  Tuning fuzzy logic controllers by genetic algorithms , 1995, Int. J. Approx. Reason..

[142]  John Yen,et al.  Industrial Applications of Fuzzy Logic and Intelligent Systems , 1995 .

[143]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.

[144]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[145]  Jaron Lanier Agents of alienation , 1995, INTR.

[146]  J. J. Shann,et al.  A fuzzy neural network for rule acquiring on fuzzy control systems , 1995 .

[147]  Victor R. Lesser,et al.  Multiagent systems: an emerging subdiscipline of AI , 1995, CSUR.

[148]  Melanie Mitchell,et al.  An introduction to genetic algorithms , 1996 .

[149]  R. W. Dobbins,et al.  Computational intelligence PC tools , 1996 .

[150]  Brian D. Ripley,et al.  Pattern Recognition and Neural Networks , 1996 .

[151]  L. Polkowski,et al.  Implementing fuzzy containment via rough inclusions: rough mereological approach to distributed problem solving , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[152]  Tsau Young Lin,et al.  Rough Sets and Data Mining: Analysis of Imprecise Data , 1996 .

[153]  J. Ross Quinlan,et al.  Bagging, Boosting, and C4.5 , 1996, AAAI/IAAI, Vol. 1.

[154]  Bart Kosko,et al.  Fuzzy Engineering , 1996 .

[155]  Marco Tomassini,et al.  Towards Evolvable Hardware: The Evolutionary Engineering Approach , 1996 .

[156]  Andrzej Skowron,et al.  Rough mereology: A new paradigm for approximate reasoning , 1996, Int. J. Approx. Reason..

[157]  Zdzisław Pawlak,et al.  ROUGH CONTROL APPLICATION OF ROUGH SET THEORY TO CONTROL , 1996 .

[158]  D. Chalmers,et al.  On the Search for the Neural Correlate of Consciousness , 1996 .

[159]  Nikola K. Kasabov,et al.  Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems , 1996, Fuzzy Sets Syst..

[160]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[161]  José M. Sánchez,et al.  Neural methods for obtaining fuzzy rules , 1996 .

[162]  Russell Beale,et al.  Handbook of Neural Computation , 1996 .

[163]  Jie Zhang,et al.  Process modelling and fault diagnosis using fuzzy neural networks , 1996, Fuzzy Sets Syst..

[164]  Marco Tomassini,et al.  A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems , 1997, IEEE Trans. Evol. Comput..

[165]  Wolfgang Banzhaf,et al.  Genetic Programming: An Introduction , 1997 .

[166]  Zbigniew W. Ras,et al.  Resolving Queries Through Cooperation in Multi-Agent Systems , 1997 .

[167]  Ian D. Watson,et al.  Applying case-based reasoning - techniques for the enterprise systems , 1997 .

[168]  James A. Reggia,et al.  Automatic discovery of self-replicating structures in cellular automata , 1997, IEEE Trans. Evol. Comput..

[169]  Tsau Young Lin,et al.  Fuzzy Controllers: An Integrated Approach Based on Fuzzy Logic, Rough Sets, and Evolutionary Computing , 1997 .

[170]  Ke Chen,et al.  Methods of Combining Multiple Classifiers with Different Features and Their Applications to Text-Independent Speaker Identification , 1997, Int. J. Pattern Recognit. Artif. Intell..

[171]  Moshe Sipper,et al.  Evolution of Parallel Cellular Machines , 1997, Lecture Notes in Computer Science.

[172]  Belur V. Dasarathy,et al.  Sensor fusion potential exploitation-innovative architectures and illustrative applications , 1997, Proc. IEEE.

[173]  Henrik Esbensen,et al.  Fuzzy/multiobjective genetic systems for intelligent systems design tools and components , 1997 .

[174]  Sherif Hashem,et al.  Optimal Linear Combinations of Neural Networks , 1997, Neural Networks.

[175]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[176]  Alan T. Schroeder Data mining with neural networks: Solving business problems from application development to decision support , 1997 .

[177]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[178]  T. Y. Lin,et al.  Rough Sets and Data Mining , 1997, Springer US.

[179]  S. Iyengar,et al.  Multi-Sensor Fusion: Fundamentals and Applications With Software , 1997 .

[180]  E. Mizutani,et al.  Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review] , 1997, IEEE Transactions on Automatic Control.

[181]  David B. Fogel,et al.  Evolutionary algorithms in theory and practice , 1997, Complex.

[182]  D. Chalmers Moving Forward on the Problem of Consciousness , 1997 .

[183]  Jeffrey Horn,et al.  Handbook of evolutionary computation , 1997 .

[184]  Shu-Cherng Fang,et al.  A genetics-based approach for aggregated production planning in a fuzzy environment , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[185]  Ching Y. Suen,et al.  Application of majority voting to pattern recognition: an analysis of its behavior and performance , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[186]  Detlef Nauck,et al.  Foundations Of Neuro-Fuzzy Systems , 1997 .

[187]  Moshe Sipper,et al.  Evolution of Parallel Cellular Machines: The Cellular Programming Approach , 1997 .

[188]  Thomas Bäck,et al.  Evolutionary computation: Toward a new philosophy of machine intelligence , 1997, Complex..

[189]  John Fulcher,et al.  Classification of User Expertise Level by Neural Networks , 1997, Int. J. Neural Syst..

[190]  D. Dasgupta,et al.  Immunity-based systems: a survey , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[191]  Jerzy W. Grzymala-Busse,et al.  MACHINE LEARNING & KNOWLEDGE ACQUISITION, ROUGH SETS, AND THE ENGLISH SEMANTIC CODE , 1997 .

[192]  Oscar Cordón,et al.  On the combination of fuzzy logic and evolutionary computation: a short review and bibliography , 1997 .

[193]  Kevin Bluff,et al.  Genetic Evolution of a Neural Network's Input Vector for Meteorological Estimations , 1997, ICONIP.

[194]  Ray R. Hashemi,et al.  A Fusion of Rough Sets, Modified Rough Sets, and Genetic Algorithms for Hybrid Diagnostic Systems , 1997 .

[195]  Chuen-Tsai Sun,et al.  Neuro-fuzzy And Soft Computing: A Computational Approach To Learning And Machine Intelligence [Books in Brief] , 1997, IEEE Transactions on Neural Networks.

[196]  Witold Pedrycz,et al.  Computational intelligence in software engineering , 1997, CCECE '97. Canadian Conference on Electrical and Computer Engineering. Engineering Innovation: Voyage of Discovery. Conference Proceedings.

[197]  Ming Zhang,et al.  Rainfall estimation using artificial neural network group , 1997, Neurocomputing.

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

[199]  Witold Pedrycz,et al.  Handbook of fuzzy computation , 1998 .

[200]  W. Pedrycz,et al.  An introduction to fuzzy sets : analysis and design , 1998 .

[201]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[202]  Witold Pedrycz,et al.  Fuzzy evolutionary computing , 1998, Soft Comput..

[203]  Jennifer Bigus,et al.  Constructing intelligent agents using JAVA , 1998 .

[204]  Bonnie A. Nardi,et al.  Collaborative, programmable intelligent agents , 1998, CACM.

[205]  L. Adleman Computing with DNA , 1998 .

[206]  James F. Peters,et al.  Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models , 1998 .

[207]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[208]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[209]  Stefan Wermter,et al.  A Novel Modular Neural Architecture for Rule-Based and Similarity-Based Reasoning , 1998, Hybrid Neural Systems.

[210]  James C. Bezdek,et al.  Computational Intelligence Defined - By Everyone ! , 1998 .

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

[212]  Witold Pedrycz,et al.  Shadowed sets: representing and processing fuzzy sets , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[213]  S. Mallat A wavelet tour of signal processing , 1998 .

[214]  James F. Allen AI Growing Up: The Changes and Opportunities , 1998, AI Mag..

[215]  Christopher J. Bishop,et al.  Pulsed Neural Networks , 1998 .

[216]  Peter Nordin,et al.  Genetic programming - An Introduction: On the Automatic Evolution of Computer Programs and Its Applications , 1998 .

[217]  Okyay Kaynak,et al.  Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications , 1998, NATO ASI Series.

[218]  David J. Miller,et al.  Critic-driven ensemble classification , 1999, IEEE Trans. Signal Process..

[219]  Robert E. King Computational intelligence in control engineering , 1999 .

[220]  Moshe Sipper,et al.  Quo Vadis evolvable hardware? , 1999, CACM.

[221]  Amanda J. C. Sharkey,et al.  Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems , 1999 .

[222]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[223]  Antanas Verikas,et al.  Soft combination of neural classifiers: A comparative study , 1999, Pattern Recognit. Lett..

[224]  Matthias Jarke Scenarios for modeling , 1999, CACM.

[225]  João Manuel Ferreira Calado,et al.  An Expert System Coupled With a Hierarchical Structure of Fuzzy Neural Networks for Fault Diagnosis , 1999 .

[226]  D. Opitz,et al.  Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..

[227]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[228]  Martyn Amos,et al.  Theoretical and Experimental DNA Computation , 1999, Bull. EATCS.

[229]  Zhengxin Chen Computational intelligence for decision support , 1999 .

[230]  Kenji Toda,et al.  Real-world applications of analog and digital evolvable hardware , 1999, IEEE Trans. Evol. Comput..

[231]  Amanda J. C. Sharkey,et al.  Boosting Using Neural Networks , 1999 .

[232]  Xin Yao,et al.  Following the path of evolvable hardware , 1999, CACM.

[233]  Kagan Tumer,et al.  An Introduction to Collective Intelligence , 1999, ArXiv.

[234]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[235]  Nicholas R. Jennings Agent-Oriented Software Engineering , 1999, MAAMAW.

[236]  Sung-Bae Cho,et al.  Pattern recognition with neural networks combined by genetic algorithm , 1999, Fuzzy Sets Syst..

[237]  Tsau Young Lin,et al.  Granular Computing: Fuzzy Logic and Rough Sets , 1999 .

[238]  P. Nordin Genetic Programming III - Darwinian Invention and Problem Solving , 1999 .

[239]  Vasile Palade,et al.  Fuzzy Computing in a MultiPurpose Neural Network Implementation , 1999, Fuzzy Days.

[240]  Xin Yao,et al.  Promises and challenges of evolvable hardware , 1996, IEEE Trans. Syst. Man Cybern. Part C.

[241]  Andrzej Skowron,et al.  Situation Identification by Unmanned Aerial Vehicle , 2000, Rough Sets and Current Trends in Computing.

[242]  Lakhmi C. Jain,et al.  Designing classifier fusion systems by genetic algorithms , 2000, IEEE Trans. Evol. Comput..

[243]  Abraham Kandel,et al.  Granular neural networks for numerical-linguistic data fusion and knowledge discovery , 2000, IEEE Trans. Neural Networks Learn. Syst..

[244]  Katia P. Sycara,et al.  Adding security and trust to multiagent systems , 2000, Appl. Artif. Intell..

[245]  Wolfgang Bibel,et al.  AI's greatest trends and controversies , 2000 .

[246]  R. T. Velde,et al.  The Age of Spiritual Machines: When Computers Exceed Human Intelligence, , 2000 .

[247]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[248]  Bernard Girau,et al.  FPNA: Interaction Between FPGA and Neural Computation , 2000, Int. J. Neural Syst..

[249]  Nicholas R. Jennings,et al.  On agent-based software engineering , 2000, Artif. Intell..

[250]  Jose C. Principe,et al.  Neural and adaptive systems : fundamentals through simulations , 2000 .

[251]  Andrew Kusiak,et al.  Computational Intelligence in Design and Manufacturing , 2000 .

[252]  Eleanor G. Rieffel,et al.  J an 2 00 0 An Introduction to Quantum Computing for Non-Physicists , 2002 .

[253]  Colin P. Williams,et al.  Ultimate zero and one - computing at the quantum frontier , 2012 .

[254]  Bo K. Wong,et al.  A bibliography of neural network business applications research: 1994-1998 , 2000, Comput. Oper. Res..

[255]  Robert Fullér,et al.  Introduction to neuro-fuzzy systems , 1999, Advances in soft computing.

[256]  Carolyn Dowling,et al.  Intelligent agents: some ethical issues and dilemmas , 2000 .

[257]  Louisa Lam,et al.  Classifier Combinations: Implementations and Theoretical Issues , 2000, Multiple Classifier Systems.

[258]  Michael Wooldridge,et al.  Agent-Oriented Software Engineering: First International Workshop, AOSE 2000 Limerick, Ireland, June 10, 2000 Revised Papers , 2001 .

[259]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[260]  Andrzej Skowron,et al.  Rough Mereological Calculi of Granules: A Rough Set Approach To Computation , 2001, Comput. Intell..

[261]  Andrzej Skowron,et al.  Toward Intelligent Systems: Calculi of Information Granules , 2001, JSAI Workshops.

[262]  R. Brooks The relationship between matter and life , 2001, Nature.

[263]  Michael Negnevitsky,et al.  Artificial Intelligence: A Guide to Intelligent Systems , 2001 .

[264]  J. Sprott Chaos and time-series analysis , 2001 .

[265]  Michael R. Chernick,et al.  Wavelet Methods for Time Series Analysis , 2001, Technometrics.

[266]  Ian Horrocks,et al.  OIL: An Ontology Infrastructure for the Semantic Web , 2001, IEEE Intell. Syst..

[267]  James F. Peters,et al.  Rough Neural Computing in Signal Analysis , 2001, Comput. Intell..

[268]  John F. Sowa,et al.  Knowledge representation: logical, philosophical, and computational foundations , 2000 .

[269]  Mübeccel Demirekler,et al.  Plurality voting-based multiple classifier systems: statistically independent with respect to dependent classifier sets , 2002, Pattern Recognit..

[270]  Tin Kam Ho,et al.  MULTIPLE CLASSIFIER COMBINATION: LESSONS AND NEXT STEPS , 2002 .

[271]  Joydeep Ghosh,et al.  Multiclassifier Systems: Back to the Future , 2002, Multiple Classifier Systems.

[272]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[273]  E. Ott Chaos in Dynamical Systems: Contents , 2002 .

[274]  Zdzislaw Pawlak,et al.  Rough sets, decision algorithms and Bayes' theorem , 2002, Eur. J. Oper. Res..

[275]  Moshe Sipper Machine Nature: The Coming Age of Bio-Inspired Computing , 2002 .

[276]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[277]  Gheorghe Paun,et al.  Membrane Computing , 2002, Natural Computing Series.

[278]  Andrzej Skowron,et al.  Towards an Ontology of Approximate Reason , 2002, Fundam. Informaticae.

[279]  Mircea Gh. Negoita,et al.  Optimization of Recurrent NN by GA with Variable Length Genotype , 2002, Australian Joint Conference on Artificial Intelligence.

[280]  Wei Tang,et al.  Ensembling neural networks: Many could be better than all , 2002, Artif. Intell..

[281]  Vasile Palade,et al.  NEURO-FUZZY BASED FAULT DIAGNOSIS APPLIED TO AN ELECTRO-PNEUMATIC VALVE , 2002 .

[282]  Ulrich Rückert,et al.  ULSI Architectures for Artificial Neural Networks , 2001, IEEE Micro.

[283]  Dr. Alex A. Freitas Data Mining and Knowledge Discovery with Evolutionary Algorithms , 2002, Natural Computing Series.

[284]  Zdzislaw Pawlak,et al.  Rough sets and intelligent data analysis , 2002, Inf. Sci..

[285]  Jan M. Zytkow,et al.  Handbook of Data Mining and Knowledge Discovery , 2002 .

[286]  Vasile Palade,et al.  FAULT DIAGNOSIS OF AN INDUSTRIAL GAS TURBINE USING NEURO-FUZZY METHODS , 2002 .

[287]  S. Tsumoto,et al.  Rough Set Theory and Granular Computing , 2003 .

[288]  Francis K. H. Quek,et al.  Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets , 2003, Pattern Recognit..

[289]  Giuseppina Gini,et al.  Neuro-fuzzy knowledge integration applied in toxicity prediction , 2003 .

[290]  James F. Peters,et al.  Rough Set Approach to Pattern Extraction from Classifiers , 2003, RSKD.

[291]  Jack Parker Computing with DNA , 2003, EMBO reports.

[292]  Robert P. W. Duin,et al.  Limits on the majority vote accuracy in classifier fusion , 2003, Pattern Analysis & Applications.

[293]  Barbara Messing,et al.  An Introduction to MultiAgent Systems , 2002, Künstliche Intell..

[294]  Steven J. Simske,et al.  Performance analysis of pattern classifier combination by plurality voting , 2003, Pattern Recognit. Lett..

[295]  L. Kuncheva ‘ Fuzzy ’ vs ‘ Non-fuzzy ’ in Combining Classifiers Designed by Boosting , 2003 .

[296]  Komwut Wipusitwarakun,et al.  Adaptive Per-application Load Balancing with Neuron-Fuzzy to Support Quality of Service for Voice over IP in the Internet , 2003, KES.

[297]  N. Azarmi,et al.  What Has AI Done for Us? , 2003 .

[298]  Ludmila I. Kuncheva,et al.  "Fuzzy" versus "nonfuzzy" in combining classifiers designed by Boosting , 2003, IEEE Trans. Fuzzy Syst..

[299]  David B. Fogel,et al.  Computational Intelligence: The Experts Speak , 2003 .

[300]  Giovanna Castellano,et al.  Discovering Prediction Rules by a Neuro-fuzzy Modeling Framework , 2003, KES.

[301]  Witold Pedrycz,et al.  Software quality analysis with the use of computational intelligence , 2003, Inf. Softw. Technol..

[302]  Georgios C. Anagnostopoulos,et al.  Knowledge-Based Intelligent Information and Engineering Systems , 2003, Lecture Notes in Computer Science.

[303]  Jack Dongarra,et al.  Sourcebook of parallel computing , 2003 .

[304]  James F. Peters,et al.  Rough Sets: Trends and Challenges , 2003, RSFDGrC.

[305]  Fabio Roli,et al.  Fusion of multiple classifiers for intrusion detection in computer networks , 2003, Pattern Recognit. Lett..

[306]  Vasile Palade,et al.  A neuro-fuzzy approach for functional genomics data interpretation and analysis , 2003, Neural Computing & Applications.

[307]  Takumi Ichimura,et al.  A Proposal of Immune Multi-agent Neural Networks and Its Application to Medical Diagnostic System for Hepatobiliary Disorders , 2003, KES.

[308]  Andrzej Skowron,et al.  A parallel algorithm for real-time decision making: A rough set approach , 1996, Journal of Intelligent Information Systems.

[309]  Seppo J. Ovaska Computationally Intelligent Hybrid Systems , 2004 .

[310]  Sun-Yuan Kung,et al.  Biometric Authentication: A Machine Learning Approach , 2004 .

[311]  Franco Zambonelli,et al.  Methodologies and software engineering for agent systems : the agent-oriented software engineering handbook , 2004 .

[312]  Michael Winikoff,et al.  Developing intelligent agent systems - a practical guide , 2004, Wiley series in agent technology.

[313]  Thomas G. Dietterich An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization , 2000, Machine Learning.

[314]  L. Jain,et al.  Fuzzy Multivariate Auto-Regression Method and its Application , 2004 .

[315]  Andrzej Skowron,et al.  Approximation Spaces and Information Granulation , 2004, Trans. Rough Sets.

[316]  Jon Rigelsford,et al.  Rough Neural Computing: Techniques for Computing with Words , 2004 .

[317]  Ludmila I. Kuncheva,et al.  Combining Pattern Classifiers: Methods and Algorithms , 2004 .

[318]  Simon C. K. Shiu,et al.  Foundations of Soft Case-Based Reasoning: Pal/Soft Case-Based Reasoning , 2004 .

[319]  Antanas Verikas,et al.  Fusing Neural Networks Through Space Partitioning and Fuzzy Integration , 2002, Neural Processing Letters.

[320]  石田 好輝 Immunity-based systems : a design perspective , 2004 .

[321]  Jeffrey W. Tweedale,et al.  Teaming Humans and Intelligent Agents , 2004 .

[322]  D. Agrafiotis,et al.  Combining particle swarms and K -nearest neighbors for the development of quantitative sturcture-activity relationships , 2004 .

[323]  John C. Gallagher,et al.  A family of compact genetic algorithms for intrinsic evolvable hardware , 2004, IEEE Transactions on Evolutionary Computation.

[324]  Joshua D. Knowles,et al.  Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects , 2004 .

[325]  Charles,et al.  Computational Intelligence in Economics and Finance , 2004, Advanced Information Processing.

[326]  Ronald,et al.  Learning representations by backpropagating errors , 2004 .

[327]  Franco Zambonelli,et al.  Methodologies and Software Engineering for Agent Systems , 2004, Multiagent Systems, Artificial Societies, and Simulated Organizations.

[328]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[329]  Lech Polkowski,et al.  Rough Mereology as a Link Between Rough and Fuzzy Set Theories. A Survey , 2004, Trans. Rough Sets.

[330]  James F. Peters,et al.  Towards a Software Change Classification System: A Rough Set Approach , 2003, Software Quality Journal.

[331]  Jared L. Cohon,et al.  Multiobjective programming and planning , 2004 .

[332]  Hung Son Nguyen,et al.  A View on Rough Set Concept Approximations , 2003, Fundam. Informaticae.

[333]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[334]  Gary Riley,et al.  Expert Systems: Principles and Programming , 2004 .

[335]  David Pritchard,et al.  A Fuzzy-Ga Hybrid Technique for Optimization of Teaching Sequences Presented in ITSs , 2004, Fuzzy Days.

[336]  Azzedine Boukerche,et al.  An artificial immune based intrusion detection model for computer and telecommunication systems , 2004, Parallel Comput..

[337]  C.J.H. Mann,et al.  Handbook of Data Mining and Knowledge Discovery , 2004 .

[338]  John McCarthy The Future of AI - A Manifesto , 2005, AI Mag..

[339]  Hod Lipson,et al.  Robotics: Self-reproducing machines , 2005, Nature.

[340]  Zdzislaw Pawlak,et al.  A Treatise on Rough Sets , 2005, Trans. Rough Sets.

[341]  Tughrul Arslan,et al.  Evolvable Components—From Theory to Hardware Implementations , 2005, Genetic Programming and Evolvable Machines.

[342]  Witold Pedrycz,et al.  Genetic granular classifiers in modeling software quality , 2005, J. Syst. Softw..

[343]  Andrzej Walczak,et al.  the Belief-Desire-Intention Model of Agency , 2005 .

[344]  Subhash C. Bagui,et al.  Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.

[345]  Witold Pedrycz Granular Computing in Knowledge Integration and Reuse , 2005, IRI.

[346]  Tong Heng Lee,et al.  Multiobjective Evolutionary Algorithms and Applications , 2005, Advanced Information and Knowledge Processing.

[347]  Marek Kisiel-Dorohinicki,et al.  Immune-Based Optimization of Predicting Neural Networks , 2005, International Conference on Computational Science.

[348]  Chang Wook Ahn,et al.  On the practical genetic algorithms , 2005, GECCO '05.

[349]  Richard J. Duro,et al.  Information Processing With Evolutionary Algorithms: From Industrial Applications To Academic Speculations (Advanced Information and Knowledge Processing) , 2005 .

[350]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[351]  How A . I . and multi-robot systems research will accelerate our understanding of social animal behavior , 2005 .

[352]  Claudio Cesar de Sá,et al.  Obtaining Membership Functions from a Neuron Fuzzy System Extended by Kohonen Network , 2005, LAPTEC.

[353]  Maya Gokhale,et al.  Reconfigurable Computing: Accelerating Computation with Field-Programmable Gate Arrays , 2005 .

[354]  Abraham Kandel,et al.  Computational Intelligence in Software Quality Assurance , 2005, Series in Machine Perception and Artificial Intelligence.

[355]  Pascal Vasseur,et al.  Introduction to Multisensor Data Fusion , 2005, The Industrial Information Technology Handbook.

[356]  Daniel Zelterman,et al.  Bayesian Artificial Intelligence , 2005, Technometrics.

[357]  R. Cronje Gladwell M. Blink: the power of thinking without thinking. Boston: Little, Brown, 2005. , 2005 .

[358]  James F. Peters,et al.  Rough Ethology: Towards a Biologically-Inspired Study of Collective Behavior in Intelligent Systems with Approximation Spaces , 2005, Trans. Rough Sets.

[359]  David Pellerin,et al.  Practical FPGA programming in C , 2005 .

[360]  Vasile Palade,et al.  Computational Intelligence - Engineering of Hybrid Systems , 2010, Studies in Fuzziness and Soft Computing.

[361]  John Fulcher,et al.  Improving the inversion of ionograms by combining neural network and data fusion techniques , 2005, Neural Computing & Applications.

[362]  Garrison W. Greenwood,et al.  Introduction to Evolvable Hardware - A Practical Guide for Designing Self-Adaptive Systems , 2006 .

[363]  Lakhmi C. Jain,et al.  Soft Computing Paradigms and Regression Trees in Decision Support Systems , 2006 .

[364]  James F. Peters,et al.  Reinforcement Learning with Approximation Spaces , 2006, Fundam. Informaticae.

[365]  H. Handa,et al.  Robust route optimization for gritting/salting trucks: a CERCIA experience , 2006, IEEE Computational Intelligence Magazine.

[366]  Andrzej Skowron,et al.  Zdzislaw Pawlak: Life and Work , 2006, Trans. Rough Sets.

[367]  Minjie Zhang,et al.  Coordinating Agent Interactions Under Open Environments , 2006 .

[368]  Noel E. Sharkey,et al.  The Application of Swarm Intelligence to Collective Robots , 2006 .

[369]  Andrzej Skowron,et al.  Rough Sets and Vague Concept Approximation: From Sample Approximation to Adaptive Learning , 2006, Trans. Rough Sets.

[370]  G. Bioul,et al.  Synthesis of Arithmetic Circuits: FPGA, ASIC and Embedded Systems , 2006 .

[371]  Shakti Kumar,et al.  Swarm Intelligence and the Taguchi Method for Identification of Fuzzy Models , 2006 .

[372]  Spike Cramphorn Blink: The Power of Thinking without Thinking / Strangers to Ourselves: Discovering the Adaptive Unconscious , 2006, Journal of Advertising Research.

[373]  Andrzej Skowron,et al.  Calculi of Approximation Spaces , 2006, Fundam. Informaticae.

[374]  James A. Hendler Introducing the Future of AI , 2006, IEEE Intell. Syst..

[375]  Qusay H. Mahmoud,et al.  Making Software Agents User-Friendly , 2006, Computer.

[376]  Jiming Liu,et al.  Toward nature-inspired computing , 2006, CACM.

[377]  Russell Beale,et al.  Knowledge Through Evolution , 2006 .

[378]  Yaochu Jin,et al.  Multi-Objective Machine Learning , 2006, Studies in Computational Intelligence.

[379]  Albert Y. Zomaya Handbook of Nature-Inspired and Innovative Computing - Integrating Classical Models with Emerging Technologies , 2006 .

[380]  Christof Teuscher Biologically uninspired computer science , 2006, CACM.

[381]  Jagath C. Rajapakse,et al.  FPGA Implementations of Neural Networks , 2006 .

[382]  J.D. Lohn,et al.  Evolvable hardware using evolutionary computation to design and optimize hardware systems , 2006, IEEE Computational Intelligence Magazine.

[383]  Nees Jan van Eck,et al.  Visualizing the computational intelligence field [Application Notes] , 2006, IEEE Computational Intelligence Magazine.

[384]  Jordan B. Pollack,et al.  Mindless Intelligence , 2006, IEEE Intelligent Systems.

[385]  Brijesh Verma,et al.  Neural Networks for the Classification of Benign and Malignant Patters in Digital Mammograms , 2006 .

[386]  Enrique Alba,et al.  Parallel Evolutionary Computations , 2006, Studies in Computational Intelligence.

[387]  Kenneth DeJong Evolutionary computation: a unified approach , 2007, GECCO.

[388]  J. Hawkins,et al.  Why Can't a Computer be more Like a Brain? , 2007, IEEE Spectrum.

[389]  Roy Sterritt,et al.  Swarms and Swarm Intelligence , 2007, Computer.

[390]  Andrzej Skowron,et al.  Rudiments of rough sets , 2007, Inf. Sci..

[391]  Lotfi A. Zadeh Granular Computing and Rough Set Theory , 2007, RSEISP.

[392]  Colin R. Reeves,et al.  Evolutionary computation: a unified approach , 2007, Genetic Programming and Evolvable Machines.

[393]  Peter Naur,et al.  Computing versus human thinking , 2007, Commun. ACM.

[394]  Salvatore Greco,et al.  Dominance-Based Rough Set Approach to Reasoning About Ordinal Data , 2007, RSEISP.

[395]  W. Neville Holmes Consciousness and Computers , 2007, Computer.

[396]  James F. Peters,et al.  Robotic Target Tracking with Approximation Space-Based Feedback During Reinforcement Learning , 2009, RSFDGrC.

[397]  Diane Crawford Stop chasing the AI illusion , 2007, CACM.

[398]  Grzegorz Rozenberg,et al.  New Frontiers in Scientific Discovery - Commemorating the Life and Work of Zdzislaw Pawlak: Book Edition of Fundamenta Informaticae , 2007 .

[399]  Włodzisław Duch,et al.  Challenges for Computational Intelligence , 2007, Studies in Computational Intelligence.

[400]  Paul P. Wang Computational Intelligence in Economics and Finance , 2007 .

[401]  Richard E. Neapolitan,et al.  Learning Bayesian networks , 2007, KDD '07.

[402]  Andrzej Skowron,et al.  Rough sets: Some extensions , 2007, Inf. Sci..

[403]  Andrzej Skowron,et al.  Rough sets and Boolean reasoning , 2007, Inf. Sci..

[404]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[405]  Wlodzislaw Duch,et al.  What Is Computational Intelligence and Where Is It Going? , 2007, Challenges for Computational Intelligence.

[406]  Carl K. Chang My Vision for Computer , 2007, Computer.