Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two ...

Cross-situational word learning is based on the notion that a learner can determine the referent of a word by finding something in common across many observed uses of that word. Here we propose an adaptive learning algorithm ...

An explanation for the acquisition of word-object mappings is the associative learning in a crosssituational scenario. Here we present analytical results of the performance of a simple associative learning algorithm for ...

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have ...

The associationist account for early word learning is based on the co-occurrence between referents and words. Here we introduce a noisy cross-situational learning scenario in which the referent of the uttered word is ...

This introductory chapter presents an overview of all contributions that summarize a decade of scientific research around science education at Cadi Ayyad University (UCA). Several practical cases have been presented and ...

This paper draws on an ethnographic case study of learning/teaching practices in Trinidad Carnival mas'camps. Over the Carnival 2005 season, selected members of the mas' making community shared their perspectives on ...