Abstract
This paper describes improvements to the rule chaining architecture presented in [1]. The architecture uses distributed associative memories to allow the system to utilise memory efficiently, and superimposed distributed representations in order to reduce the time complexity of a tree search to O(d), where d is the depth of the tree. This new work reduces the memory required by the architecture, and can also further reduce the time complexity.
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Burles, N., O’Keefe, S., Austin, J. (2013). Improving the Associative Rule Chaining Architecture. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_13
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DOI: https://doi.org/10.1007/978-3-642-40728-4_13
Publisher Name: Springer, Berlin, Heidelberg
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