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
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
Situated grounded word semantics
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
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
The Acquisition of Linguistic Competence for Communicating Propositional Logic Sentences
Engineering Societies in the Agents World VIII
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Verifying Theories of Language Acquisition Using Computer Models of Language Evolution
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Group size effects on the emergence of compositional structures in language
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Co-learning and the development of communication
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Modeling social learning of language and skills
Artificial Life
Towards representational autonomy of agents in artificial environments
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Cumulative cultural evolution: can we ever learn more?
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
A hybrid model for learning word-meaning mappings
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
Cooperation, conceptual spaces and the evolution of semantics
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
Propositional logic syntax acquisition
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
Simulating meaning negotiation using observational language games
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
Autonomous construction of ecologically and socially relevant semantics
Cognitive Systems Research
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Individual semiosis in multi-agent systems
Transactions on Computational Collective Intelligence VII
| Hi-index | 0.00 |
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.