  I pinpoint an interesting similarity between a recent account to rational
parsing and the treatment of sequential decisions problems in a dynamical
systems approach. I argue that expectation-driven search heuristics aiming at
fast computation resembles a high-risk decision strategy in favor of large
transition velocities. Hale's rational parser, combining generalized
left-corner parsing with informed $\mathrm{A}^*$ search to resolve processing
conflicts, explains gardenpath effects in natural sentence processing by
misleading estimates of future processing costs that are to be minimized. On
the other hand, minimizing the duration of cognitive computations in
time-continuous dynamical systems can be described by combining vector space
representations of cognitive states by means of filler/role decompositions and
subsequent tensor product representations with the paradigm of stable
heteroclinic sequences. Maximizing transition velocities according to a
high-risk decision strategy could account for a fast race even between states
that are apparently remote in representation space.
