Managing Interference Between Prior and Later Learning

A device algorithm which permanently records an expanding portfolio of similar conditions is described, along with an architecture in which this algorithm is used to avoid interference between prior and later learning.

[1]  L. Andrew Coward.  The recommendation architecture: lessons from large-scale electronic systems applied to cognition , 2001, Cognitive Systems Research.

[2]  Tom Gedeon,et al.  Application of the Recommendation Architecture for discovering associative similarities in text , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

[3]  Gary J. Chastek,et al.  A Case Study in Structural Modeling , 1996 .

[4]  Anthony V. Robins,et al.  Catastrophic Forgetting, Rehearsal and Pseudorehearsal , 1995, Connect. Sci..

[5]  L. Andrew Coward.  Accounting for Episodic, Semantic and Procedural Memory in the Recommendation Architecture Cognitive Model , 2005 .

[6]  Ragui Kamel,et al.  Effect of Modularity on System Evolution , 1987, IEEE Software.

[7]  L. Andrew Coward.  A System Architecture Approach to the Brain: From Neurons to Consciousness , 2005 .

[8]  Paul Clements,et al.  Software architecture in practice , 1999, SEI series in software engineering.

[9]  L. A. Coward,et al.  The Recommendation Architecture Model for Human Cognition , 2004 .

[10]  R. French.  Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.

[11]  Tamás D. Gedeon,et al.  Application of the Recommendation Architecture to Telecommunications Network Management , 2001, Int. J. Neural Syst..

[12]  José Carlos Príncipe,et al.  Information Theoretic Clustering , 2002, IEEE Trans. Pattern Anal. Mach. Intell..