A dynamical systems approach to parsing is proposed in which syntactic hypotheses are associated with attractors in a metric space. These attractors have many of the properties of traditional syntactic categories, while at the same time encoding context-dependent, lexically speci�c distinctions. Hypotheses motivated by the dynamical system theory were tested in four reading time experiments examining the interaction of simple lexical frequencies, frequencies that are contingent on an environment de�ned by syntactic categories, and frequencies contingent on verb argument structure. The experiments documented a variety of contingent frequency effects that cut across traditional linguistic grains, each of which was predicted by the dynamical systems model. These effects were simulated in an implementation of the theory, employing a recurrent network trained from a corpus to construct metric representations and an algorithm implementing a gravitational dynamical system to model reading time as time to gravitate to an attractor
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