The Horse Raced Past: Gardenpath Processing in Dynamical Systems

TL;DR

This paper explores the parallels between rational parsing models and dynamical systems, proposing that expectation-driven heuristics and high transition velocities can explain rapid and complex sentence processing phenomena.

Contribution

It introduces a novel connection between rational parsing and dynamical systems, suggesting that high-risk decision strategies and transition velocities can model gardenpath effects.

Findings

Rational parser models explain gardenpath effects via misleading cost estimates.

Dynamical systems with high transition velocities can account for rapid cognitive state changes.

The approach unifies linguistic parsing with dynamical systems theory.

Abstract

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.