Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/30065

Title

New neural multiprocess memory model for adaptively regulating associative learning

Author(s)

Rogers, Brendan L.

Abstract

This article describes the development, operation, and behaviour of the neural multiprocess memory model (NMMM). The NMMM is a new artificial synaptic multistage memory system that replaces the single associative long-term memory that normally modulates the efficacy of artificial neural network (ANN) element inputs. The NMMM enhances learning in an ANN element by supporting multiple time scales in the acquisition, retention, and recall of encoded associative memory traces, and by appropriately modulating the learning rate based upon previous learning experience over many trials. Presented computer simulation results indicate that the NMMM on its own supports spontaneous regression and recovery behaviour and U-shaped memory retention, and that when functioning as part of the associative conditioning element (ACE), the NMMM's new adaptive associability mechanism is capable of supporting both negatively accelerated and sigmoidal acquisition curves, latent inhibition, learned irrelevance, the partial reinforcement effect, and accelerated learning following alternating acquisition-extinction training sessions.

Publication type

Journal article

Research centre

Swinburne University of Technology. School of Mechanical and Manufacturing Engineering

Source

Neural Networks, Vol. 7, no. 9 (1994), p. 1351-1378

Publication year

1994

Keyword(s)

Artificial neural networks;  Associability;  Associative conditioning element;  Classical conditioning;  Consolidation;  Long-term memory;  Medium-term memory;  Neural multiprocess memory model;  NMMM;  Short-term memory

Publisher

Elsevier

ISSN

0893-6080

Publisher URL

http://dx.doi.org/10.1016/0893-6080(94)90085-X

Copyright

Copyright © 1994 Published by Elsevier Science Ltd.

Peer reviewed