Developing concept representations

Authors:
Stathis Kasderidis
Affiliations:
Foundation for Research and Technology Hellas, Institute of Computer Science, Heraklion, Greece
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

Citing 3
Cited 1

Conceptual Spaces: The Geometry of Thought

Conceptual Spaces: The Geometry of Thought
A self-organizing neural model of motor equivalent reaching and tool use by a multijoint arm

Journal of Cognitive Neuroscience
Improved heterogeneous distance functions

Journal of Artificial Intelligence Research

A hierarchical attention-based neural network architecture, based on human brain guidance, for perception, conceptualisation, action and reasoning

Image and Vision Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper discusses a novel model for concept learning and representation. Two levels of representation are used: exemplars and (generalized concepts) prototypes. The internal structure of the model is based on a semantic network using spreading activation. Categorisation and addition operations are supported in parallel. Forgetting of learned concepts is used in order to track dynamic and novel environments. The model is inspired by the corresponding psychological theories of exemplars and prototypes. Simulation results support the formulation of the model.