On the Knowledge Organization in Concept Formation: An Exploratory Cognitive Modeling Study
Recent cognitive modeling studies suggest the effectiveness of meta-heuristic optimization in describing human cognitive behaviors. Such models are built on the basis of population-based algorithm (e.g., genetic algorithm) and thus hold multiple solutions or notions. There are, however, important yet unaddressed issues in cognitive mechanisms associated with possession of multiple notions. The issues we address in the present research is about how multiple notions are organized in our mind. In particular, we paid close attention to how each notion interact with other notions while learning a new concept. In so doing, we incorporated Particle Swarm Optimization in a cognitive model of concept learning. Three PSO-based concept learning models were developed and compared in the present exploratory cognitive modeling study.
KeywordsParticle Swarm Optimization Concept Formation Swarm Intelligence Concept Learning Knowledge Organization
Unable to display preview. Download preview PDF.
- 1.Anderson, J.R.: The Adaptive Character of Thought. Lawrence Erlbaum, Hillsdale (1990)Google Scholar
- 3.Engelbrecht, A.P.: Fundamentals of Computational Swarm Intelligence. Wilely, Chichester (2005)Google Scholar
- 4.Gigerenzer, G., Todd, P.M., The ABC Research Group: Simple heuristics that make us smart. Oxford, New York (1999)Google Scholar
- 5.Higashi, H., Iba, H.: Particle Swarm Optimization with Gaussian Mutation. In: Proceedings of the IEEE Swarm Intelligence Symposium, pp. 72–79 (2003)Google Scholar
- 6.Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm Intelligence. Morgan Kaufmann, San Francisco (2001)Google Scholar