manuscript available: Feature-based induction

[sloman%meme@Forsythe.Stanford.EDU]

A compressed postscript version of the following paper has been placed
in the pub/neuroprose directory for anonymous ftp from
cheops.cis.ohio-state.edu.  The paper concerns a very simple
connectionist model (n inputs, one output, and delta-rule learning) of
people's willingness to affirm a property of one natural-kind category
given confirmation of the property in other categories.  The paper has
been submitted for publication.


                        Feature-Based Induction

                           Steven A. Sloman
                          Dept. of Psychology
                        University of Michigan

                    e-mail: sloman at psych.stanford.edu

                                Abstract

A connectionist model of argument strength is proposed that applies to
categorical arguments involving natural categories and predicates
about which subjects have few prior beliefs.  An example is *robins
have sesamoid bones, therefore falcons have sesamoid bones*.  The model
is based on the hypotheses that argument strength (i) increases with
the overlap between features of the combined premise categories and
features of the conclusion category; and (ii) decreases with the
amount of prior knowledge about the conclusion category.  The model
assumes a two-stage process.  First, premises are encoded by
connecting the features of premise categories to the predicate.
Second, conclusions are tested by examining the degree of activation
of the predicate upon presentation of the features of the conclusion
category.  The model accounts for 13 qualitative phenomena and shows
close quantitative fits to several sets of argument-strength ratings.