Perceptually grounded lexicon formation using inconsistent knowledge

Authors:
Federico Divina;Paul Vogt
Affiliations:
Computational Linguistics and AI Section, Tilburg University, Tilburg, The Netherlands;Computational Linguistics and AI Section, Tilburg University, Tilburg, The Netherlands
Venue:
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Year:
2005

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Abstract

Typically, multi-agent models for studying the evolution of perceptually grounded lexicons assume that agents perceive the same set of objects, and that there is either joint attention, corrective feedback or cross-situational learning. In this paper we address these two assumptions, by introducing a new multi-agent model for the evolution of perceptually grounded lexicons, where agents do not perceive the same set of objects, and where agents receive a cue to focus their attention to objects, thus simulating a Theory of Mind. In addition, we vary the amount of corrective feedback provided to guide learning word-meanings. Results of simulations show that the proposed model is quite robust to the strength of these cues and the amount of feedback received.