Abstract
This paper surveys several non-deterministic modelling
techniques and places them in a uniform framework. Three basically different methods
are discussed: enumeration and evaluation of possible models; reduction
of a large model by coalescing states; and limited-context methods
which analyse and process all strings of a given length which occur
in the behaviour.
Three results of recent work are presented. Firstly, the methodology of
enumeration and evaluation is extended to the case where the model space
permits recursion. Secondly, some new experiments on successive
reduction of large models are described, which indicate that the quality of models
produced by this technique is rather variable. Thirdly, it is shown that
limited context methods which discard information about transitions
cannot identify certain kinds of inputs. However, they can take advantage of
assistance from a "teacher" in the form of markers in the input string.
Notes
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