CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The Induction of Dynamical Recognizers
Machine Learning - Connectionist approaches to language learning
A dynamical systems perspective on agent-environment interaction
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
Neural Networks - Special issue on organisation of computation in brain-like systems
An Behavior-based Robotics
The emergence of linguistic structure: an overview of the iterated learning model
Simulating the evolution of language
Grounding symbols through evolutionary language games
Simulating the evolution of language
The mirror system, imitation, and the evolution of language
Imitation in animals and artifacts
Imitation: a means to enhance learning of a synthetic protolanguage in autonomous robots
Imitation in animals and artifacts
Semantic Lexicon Acquisition for Learning Natural Language Interfaces
Semantic Lexicon Acquisition for Learning Natural Language Interfaces
Grounding the lexical semantics of verbs in visual perception using force dynamics and event logic
Journal of Artificial Intelligence Research
Model-based learning for mobile robot navigation from the dynamicalsystems perspective
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Self-organization of behavioral primitives as multiple attractor dynamics: A robot experiment
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
Learning object-manipulation verbs for human-robot communication
Proceedings of the 2007 workshop on Multimodal interfaces in semantic interaction
Neural Information Processing
Acquiring a Functionally Compositional System of Goal-Directed Actions of a Simulated Agent
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Incremental learning of integrated semiotics based on linguistic and behavioral symbols
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Integrative learning between language and action: a neuro-robotics experiment
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Recognition and generation of sentences through self-organizing linguistic hierarchy using MTRNN
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Robot trajectory prediction and recognition based on a computational mirror neurons model
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Simultaneously emerging Braitenberg codes and compositionality
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Robots that learn language: developmental approach to human-machine conversations
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
| Hi-index | 0.00 |
We present a novel connectionist model for acquiring the semantics of a simple language through the behavioral experiences of a real robot. We focus on the "compositionality" of semantics and examine how it can be generated through experiments. Our experimental results showed that the essential structures for situated semantics can self-organize themselves through dense interactions between linguistic and behavioral processes whereby a certain generalization in learning is achieved. Our analysis of the acquired dynamical structures indicates that an equivalence of compositionality appears in the combinatorial mechanics self-organized in the neuronal nonlinear dynamics. The manner in which this mechanism of compositionality, based on dynamical systems, differs from that considered in conventional linguistics and other synthetic computational models, is discussed in this paper.