Cross-situational Learning Research Articles

A computational study of cross-situational techniques for learning word-to-meaning mappings

This paper presents a computational study of part of the lexical-acquisition task faced by children, namely the acquisition of word-to-meaning mappings. It first approximates this task as a formal mathematical problem. It then presents an implemented algorithm for solving this problem, illustrating its operation on a small example. This algorithm offers one precise interpretation of the intuitive notions of cross-situational learning and the principle of contrast applied between words in an utterance. It robustly learns a homonymous lexicon despite noisy multi-word input, in the presence of referential uncertainty, with no prior knowledge that is specific to the language being learned. Computational simulations demonstrate the robustness of this algorithm and illustrate how algorithms based on cross-situational learning and the principle of contrast might be able to solve lexical-acquisition problems of the size faced by children, under weak, worst-case assumptions about the type and quantity of data available.

A Social-Psychological Analysis of Modernization in the Philippines

Four field studies of aspects of modernization in the Philippines are summarized: transitory ownership of space in a city, the development of the fishing industry in a provincial town, the practices of market vendors, and the development of modern attitudes. Processes of change and resistance are interpreted with reference to laboratory studies of cross-situational consistency, gaming strategies, avoidance learning, and operant conditioning.