What is the type-1/type-2 distinction?

Clark & Thornton's type-1/-2 distinction is not well-defined. The classes of type-1 and type-2 problems are too broad: many nocomputable functions are type-1 and type-2 learnable. They are also too narrow: trivial functions, such as identity, are neither type-1 nor type-2 learnable. Moreover, the scope of type-1 and type-2 problems appears to be equivalent. Overall, this distinction does not appear useful for machine learning or cognitive science.

[1]  J. Bullinaria.  Modeling Reading, Spelling, and Past Tense Learning with Artificial Neural Networks , 1997, Brain and Language.

[2]  Peter Ford Dominey,et al.  Analogical transfer is effective in a serial reaction time task in Parkinson's disease: Evidence for a dissociable form of sequence learning , 1997, Neuropsychologia.

[3]  R. K. Thompson,et al.  Language-naive chimpanzees (Pan troglodytes) judge relations between relations in a conceptual matching-to-sample task. , 1997, Journal of experimental psychology. Animal behavior processes.

[4]  John Preston,et al.  The Engine of Reason, The Seat of the Soul: A Philosophical Journey into the Brain , 1996 .

[5]  Stellan Ohlsson,et al.  Learning from Performance Errors. , 1996 .

[6]  Vivienne B. Carr,et al.  The acquisition of knowledge. , 1996, American journal of orthopedics.

[7]  Philip E. Agre,et al.  Computation and Embodied Agency , 1997, Informatica.

[8]  Peter Ford Dominey,et al.  Analogical Transfer in Sequence Learning. , 1995, Annals of the New York Academy of Sciences.

[9]  Gary F. Marcus,et al.  German Inflection: The Exception That Proves the Rule , 1995, Cognitive Psychology.

[10]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[11]  T. Gelder,et al.  What Might Cognition Be, If Not Computation? , 1995 .

[12]  Peter Ford Dominey,et al.  A Model of Corticostriatal Plasticity for Learning Oculomotor Associations and Sequences , 1995, Journal of Cognitive Neuroscience.

[13]  Istvan S. N. Berkeley.  Density Plots of Hidden Value Unit Activations Reveal Interpretable Bands , 1995, Connect. Sci..

[14]  L. Henderson,et al.  Serial reaction time learning and Parkinson's disease: Evidence for a procedural learning deficit , 1995, Neuropsychologia.

[15]  Thomas R. Shultz,et al.  Modeling cognitive development with a generative connectionist algorithm , 1995 .

[16]  David Kirsh,et al.  The Intelligent Use of Space , 1995, Artif. Intell..

[17]  I. Kononenko,et al.  INDUCTION OF DECISION TREES USING RELIEFF , 1995 .

[18]  Robert S. Stufflebeam.  Representations, Explanations, and PDP: Is Representation-Talk Really Necessary? , 1995, Informatica.

[19]  Jon Oberlander,et al.  A Cognitive Theory of Graphical and Linguistic Reasoning: Logic and Implementation , 1995, Cogn. Sci..

[20]  J. Elman,et al.  Default Generalization in Connectionist Networks , 1995 .

[21]  A. Vinter,et al.  Is there an implicit level of representation? , 1994, Behavioral and Brain Sciences.

[22]  Paul P. Maglio,et al.  On Distinguishing Epistemic from Pragmatic Action , 1994, Cogn. Sci..

[23]  Robert L. Goldstone.  The role of similarity in categorization: providing a groundwork , 1994, Cognition.

[24]  Lauretta M. Reeves,et al.  The Role of Content and Abstract Information in Analogical Transfer , 1994 .

[25]  Roger W. Schvaneveldt,et al.  What Is Learned From Artificial Grammars? Transfer Tests of Simple Association , 1994 .

[26]  Bob Welham.  What computers still can’t do: a critique of artificial reason , 1994 .

[27]  Ron Sun,et al.  Computational Architectures Integrating Neural And Symbolic Processes , 1994 .

[28]  Douglas L. Medin,et al.  On the Interaction of Theory and Data in Concept Learning , 1994, Cogn. Sci..

[29]  P. Thagard,et al.  Explanatory coherence , 1993 .

[30]  A. Karmiloff-Smith,et al.  What's Special about the Development of the Human Mind/Brain? , 1993 .

[31]  A. Karmiloff-Smith,et al.  The cognizer's innards: A psychological and philosophical perspective on the development of thought. , 1993 .

[32]  Kenneth D. Forbus,et al.  The Roles of Similarity in Transfer: Separating Retrievability From Inferential Soundness , 1993, Cognitive Psychology.

[33]  J. Elman.  Learning and development in neural networks: the importance of starting small , 1993, Cognition.

[34]  Ian Cloete,et al.  Increased Complexity Training , 1993, IWANN.

[35]  P. T. Szymanski,et al.  Adaptive mixtures of local experts are source coding solutions , 1993, IEEE International Conference on Neural Networks.

[36]  Andy Clark,et al.  Associative Engines: Connectionism, Concepts, and Representational Change , 1993 .

[37]  Anne Wilson,et al.  Linking Symbolic and Subsymbolic Computing , 1993 .

[38]  Philip E. Agre,et al.  The Symbolic Worldview: Reply to Vera and Simon , 1993, Cogn. Sci..

[39]  Stephen I. Gallant,et al.  Neural network learning and expert systems , 1993 .

[40]  Terrence J. Sejnowski,et al.  The Computational Brain , 1996, Artif. Intell..

[41]  David J. C. MacKay,et al.  A Practical Bayesian Framework for Backpropagation Networks , 1992, Neural Computation.

[42]  Michael R. W. Dawson,et al.  Modifying the Generalized Delta Rule to Train Networks of Non-monotonic Processors for Pattern Classification , 1992 .

[43]  Michelene T. H. Chi,et al.  Conceptual Change within and across Ontological Categories: Examples from Learning and Discovery in Science , 1992 .

[44]  Anders Krogh,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[45]  Anders Krogh,et al.  A Simple Weight Decay Can Improve Generalization , 1991, NIPS.

[46]  J. W. Rudy,et al.  Elemental and configural associations, the hippocampus and development , 1991 .

[47]  U. Goswami.  Analogical Reasoning: What Develops? A Review of Research and Theory. , 1991 .

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

[49]  Richard Lippmann,et al.  Neural Network Classifiers Estimate Bayesian a posteriori Probabilities , 1991, Neural Computation.

[50]  Mark T. Keane,et al.  Cognitive Psychology: A Student's Handbook , 1990 .

[51]  Pierre Perruchet,et al.  A critical reappraisal of the evidence for unconscious abstraction of deterministic rules in complex experimental situations , 1990, Cognitive Psychology.

[52]  Karl Haberlandt,et al.  Expose hidden assumptions in network theory , 1990, Behavioral and Brain Sciences.

[53]  Peter M. Duppenthaler.  Maturational Constraints on Language Learning , 1990 .

[54]  Michael I. Jordan,et al.  Task Decomposition through Competition in A , 1990 .

[55]  H. White.  Some Asymptotic Results for Learning in Single Hidden-Layer Feedforward Network Models , 1989 .

[56]  David Haussler,et al.  What Size Net Gives Valid Generalization? , 1989, Neural Computation.

[57]  Christian Lebiere,et al.  The Cascade-Correlation Learning Architecture , 1989, NIPS.

[58]  Stellan Ohlsson,et al.  An Information Processing Analysis of the Function of Conceptual Understanding in the Learning of Arithmetic Procedures. , 1988 .

[59]  R. K. Lindsay.  Images and inference , 1988, Cognition.

[60]  James L. McClelland,et al.  Explorations in parallel distributed processing: a handbook of models, programs, and exercises , 1988 .

[61]  Pawel Lewicki,et al.  Acquisition of procedural knowledge about a pattern of stimuli that cannot be articulated , 1988, Cognitive Psychology.

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

[63]  Terrence J. Sejnowski,et al.  NETtalk: a parallel network that learns to read aloud , 1988 .

[64]  W. Brewer,et al.  Theories of Knowledge Restructuring in Development , 1987 .

[65]  M. Nissen,et al.  Attentional requirements of learning: Evidence from performance measures , 1987, Cognitive Psychology.

[66]  Eric B. Baum,et al.  Supervised Learning of Probability Distributions by Neural Networks , 1987, NIPS.

[67]  R. Gold.  The Description of Cognitive Development: Three Piagetian Themes , 1987 .

[68]  Terrence J. Sejnowski,et al.  Parallel Networks that Learn to Pronounce , 1987 .

[69]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987, Cogn. Sci..

[70]  Terrence J. Sejnowski,et al.  Parallel Networks that Learn to Pronounce English Text , 1987, Complex Syst..

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

[72]  Arthur C. Graesser,et al.  Effects of task and new arguments on word reading times , 1986 .

[73]  Geoffrey E. Hinton,et al.  Learning and relearning in Boltzmann machines , 1986 .

[74]  D. Medin,et al.  The role of theories in conceptual coherence. , 1985, Psychological review.

[75]  Leslie G. Valiant,et al.  A theory of the learnable , 1984, CACM.

[76]  Sharon Lee Armstrong,et al.  What some concepts might not be , 1983, Cognition.

[77]  K. Holyoak,et al.  Schema induction and analogical transfer , 1983, Cognitive Psychology.

[78]  Thomas G. Dietterich,et al.  Learning and Inductive Inference , 1982 .

[79]  A G Barto,et al.  Toward a modern theory of adaptive networks: expectation and prediction. , 1981, Psychological review.

[80]  K. Holyoak,et al.  Analogical problem solving , 1980, Cognitive Psychology.

[81]  Brian V. Funt,et al.  Problem-Solving with Diagrammatic Representations , 1980, Artif. Intell..

[82]  R. Rescorla.  A theory of pavlovian conditioning: The effectiveness of reinforcement and non-reinforcement , 1972 .

[83]  K. Maccorquodale.  ON CHOMSKY'S REVIEW OF SKINNER'S VERBAL BEHAVIOR , 1970 .

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

[85]  George A. Miller,et al.  Introduction to the Formal Analysis of Natural Languages , 1968 .

[86]  G. A. Miller.  THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .