We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…

This paper describes a set of simulations which explore the way different features of lexical organisation affect the probability of finding a pair of associated words in a set of five randomly selected words. The simulation is equivalent to giving Ss a set of five words and asking if they can identify a pair of associated words among them. The…