How much computational resource is needed for the human brain to comprehend a sentence? This paper argues for
divergences between adults and children in pronoun resolution to be due to differences in computational resources, and not to fundamentally different mechanisms.
In their experiments, Hendriks, Spenader and colleagues (e.g., forthcoming in Journal of Child Language) asked children
to decide whether a sentence describe correctly a picture. An image depicting an alligator and an elephant with the
second hitting himself was accompanied by the sentence 'the elephant hits him'. Surprisingly for an adult speaker,
children tended to accept the sentence as correctly describing the scene, even though the same children would
spontaneously use the reflexive 'himself' if asked to produce a sentence recounting the drawing. Why do children accept
personal pronouns with a reflexive interpretation?
Hendriks et al. employed bi-directional Optimality Theory to describe the phenomenon and they argued that young
children lacking a theory of mind (the capability to read others' mind) are also unable to optimise bi-directionally.
Without questioning the validity of their account, this talk will present an alternative explanation, which is based on
the Simulated Annealing for Optimality Theory Algorithm. The model, analogous to the one employed for voice
assimilation by Biro (2006, chapter 6), predicts a 50% error rate, unless an infinite amount of seemingly useless
candidates are also taken into account. Hence, we argue, adults' mental computation differ from children's not by a
different optimisation technique, rather by a wealthier candidate set.