A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf
.
A self-organizing approach to episodic memory modeling
2010
The 2010 International Joint Conference on Neural Networks (IJCNN)
This paper presents a neural model that learns episodic traces in response to a continual stream of sensory input and feedback received from the environment. The proposed model, based on fusion Adaptive Resonance Theory (fusion ART) network, extracts key events and encodes spatiotemporal relations between events by creating cognitive nodes dynamically. The model further incorporates a novel memory search procedure, which performs parallel search of stored episodic traces continuously. Comparing
doi:10.1109/ijcnn.2010.5596734
dblp:conf/ijcnn/WangSTS10
fatcat:37tkeagw5zb5vbzcggaajl5d3m