19 Parallel and Serial Methods of Pattern Matching D. J. Willshaw and 0. P. Buneman

AI Classics/files/AI/classics/Machine_Intelligence_7/MI-7-Ch19-WillshawBuneman.pdf 

We describe how to design simple contentaddressable memories, functioning in parallel, which can do this and which, in some sense, can generalise about the stored data. Secondly, we consider how certain graphical representations of data may be suitable for use in efficient serial search strategies. We indicate how such structures can be used in diagnosis when the availability or cost of tests to be applied cannot be determined in advance. The type of parallel system to be considered is to store descriptions of a set of patterns, and is then to be used to supplement an incomplete description of a newly presented pattern by matching it against those in store. If this partial description matches one or more of the stored patterns then we would like the memory to provide us with the partial description that these patterns share. If the new pattern does not match any in store then we expect that the information supplied will be according to the relationships between the pattern presented and those in store. The information that we require our memory to provide when given an incomplete description as an address is therefore more than just the response'yes' or'no'. In this respect our type of system differs from content-addressable parallel memories used in computer technology, and for the same reason its capabilities exceed that of a switching network which is designed to respond positively when the states of its input channels attain one of a number of combinations of binary values (Richards 1971, Renwick and Cole 1971). This paper generalises the work of Willshaw (1972) to ensembles which conform to few or no logical constraints.

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