On the nature of explanation: a PDP approach

[1]  Peter Lipton,et al.  Inference to the best explanation , 1993 .

[2]  Terrence J. Sejnowski,et al.  Learned classification of sonar targets using a massively parallel network , 1988, IEEE Trans. Acoust. Speech Signal Process..

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

[4]  Paul M. Churchland,et al.  Some reductive Strategies in Cognitive Neurobiology , 1986, The Philosophy of Artificial Intelligence.

[5]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[6]  H. Ridley.  Eye and Brain , 1973 .

[7]  H. Putnam.  IS SEMANTICS POSSIBLE , 1970 .

[8]  M. Posner,et al.  On the genesis of abstract ideas. , 1968, Journal of experimental psychology.

[9]  T. Kuhn,et al.  The Structure of Scientific Revolutions , 1963 .

[10]  C. Hempel,et al.  Studies in the Logic of Explanation , 1948, Philosophy of Science.

[11]  P. Churchland.  On the nature of theories: a neurocomputational perspective , 1990 .

[12]  P. Churchland.  A Neurocomputational Perspective: The Nature of Mind and the Structure of Science , 1989 .

[13]  Roger C. Schank,et al.  SCRIPTS, PLANS, GOALS, AND UNDERSTANDING , 1988 .

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

[15]  George Lakoff,et al.  Women, Fire, and Dangerous Things , 1987 .

[16]  I. Rock.  The Logic of Perception , 1983 .

[17]  R. Gregory.  The intelligent eye , 1970 .

[18]  G. Harman.  The Inference to the Best Explanation , 1965 .

[19]  C. K. Ogden,et al.  The Meaning of Meaning , 1923 .