Bayesian learning of probabilistic language models
Bayesian learning of probabilistic language models
Forgetting Exceptions is Harmful in Language Learning
Machine Learning - Special issue on natural language learning
Simulating the evolution of language
Simulating the evolution of language
The emergence of linguistic structure: an overview of the iterated learning model
Simulating the evolution of language
Natural language from artificial life
Artificial Life
Situated Grounded Word Semantics
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Unsupervised language acquisition
Unsupervised language acquisition
Compositional Syntax From Cultural Transmission
Artificial Life
Constructivist development of grounded construction grammars
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Meaning development versus predefined meanings in language evolution models
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IEEE Transactions on Evolutionary Computation
The physical symbol grounding problem
Cognitive Systems Research
Joint attention and language evolution
Connection Science - Social Learning in Embodied Agents
The Iterated Classification Game: A New Model of the Cultural Transmission of Language
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Semantic networks -based teachable agents in an educational game
WSEAS Transactions on Computers
Teachable characters: semantic neural networks in game AI
NN'09 Proceedings of the 10th WSEAS international conference on Neural networks
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This paper describes a new model on the evolution and induction of compositional structures in the language of a population of (simulated) robotic agents. The model is based on recent work in language evolution modelling, including the iterated learning model, the language game model and the Talking Heads experiment. It further adopts techniques recently developed in the field of grammar induction. The paper reports on a number of different experiments done with this new model and shows certain conditions under which compositional structures can emerge. The paper confirms previous findings that a transmission bottleneck serves as a pressure mechanism for the emergence of compositionality, and that a communication strategy for guessing the references of utterances aids in the development of qualitatively 'good' languages. In addition, the results show that the emerging languages reflect the structure of the world to a large extent and that the development of a semantics, together with a competitive selection mechanism, produces a faster emergence of compositionality than a predefined semantics without such a selection mechanism.