Sequential Memory with ART: A Self-Organizing Network Capable of Learning Sequences of Patterns
| Data(s) |
14/11/2011
14/11/2011
01/01/1993
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| Resumo |
A model which extends the adaptive resonance theory model to sequential memory is presented. This new model learns sequences of events and recalls a sequence when presented with parts of the sequence. A sequence can have repeated events and different sequences can share events. The ART model is modified by creating interconnected sublayers within ART's F2 layer. Nodes within F2 learn temporal patterns by forming recency gradients within LTM. Versions of the ART model like ART I, ART 2, and fuzzy ART can be used. |
| Identificador | |
| Idioma(s) |
en_US |
| Publicador |
Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems |
| Relação |
BU CAS/CNS Technical Reports;CAS/CNS-TR-1993-033 |
| Direitos |
Copyright 1993 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission. Boston University Trustees |
| Tipo |
Technical Report |
