Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP0773794
Funding Status
Closed
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Funded Activity Summary
Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure presents the opportunity to discover how an intelligent thinking system should operate. In addition, many important problems facing an information economy involve being able to understand how people behave. An understanding of the concepts people use is central to this endeavour.Funded Activity Details
Start Date: 2007
End Date: 12-2011
Funding Scheme: Discovery Projects
Funding Amount: $510,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Psychology | Learning, Memory, Cognition And Language | Knowledge Representation And Machine Learning | Applied Statistics
