Building concepts for AI agents using information theoretic co-clustering
High level conceptual thought seems to be at the basis of the impressive human cognitive ability, and AI researchers aim to replicate this ability in artificial agents. Classical top-down (Logic based) and bottom-up (Connectionist) approaches to the problem have had limited success to date. We review a small body of work that represents a different approach to AI. We call this work the Bottom Up Symbolic (BUS) approach and present a new BUS method to concept construction. While valid concepts...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010|
|01_Chen_Building_concepts_for_AI_2010.pdf||156 kB||Adobe PDF||Request a copy|
|02_Chen_Building_concepts_for_AI_2010.pdf||20.87 kB||Adobe PDF||Request a copy|
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