A cross-situational algorithm for learning a lexicon using neural modeling fields
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Emotions, language, and Sapir-Whorf hypothesis
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Emotional cognitive agents with adaptive ontologies
AIS-ADM'07 Proceedings of the 2nd international conference on Autonomous intelligent systems: agents and data mining
Language and cognition interaction neural mechanisms
Computational Intelligence and Neuroscience
Journal of Global Information Management
| Hi-index | 0.00 |
Evolutionary language games have proved a useful tool to study the evolution of communication codes in communities of agents that interact among themselves by transmitting and interpreting a fixed repertoire of signals. Most studies have focused on the emergence of Saussurean codes (i.e., codes characterized by an arbitrary one-to-one correspondence between meanings and signals). In this contribution, we argue that the standard evolutionary language game framework cannot explain the emergence of compositional codes-communication codes that preserve neighborhood relationships by mapping similar signals into similar meanings-even though use of those codes would result in a much higher payoff in the case that signals are noisy. We introduce an alternative evolutionary setting in which the meanings are assimilated sequentially and show that the gradual building of the meaning-signal mapping leads to the emergence of mappings with the desired compositional property.