Systematicity in sentence processing with a recursive self-organizing neural network
نویسندگان
چکیده
As potential candidates for human cognition, connectionist models of sentence processing must learn to behave systematically by generalizing from a small traning set. It was recently shown that Elman networks and, to a greater extent, echo state networks (ESN) possess limited ability to generalize in artificial language learning tasks. We study this capacity for the recently introduced recursive self-organizing neural network model and show that its performance is comparable with ESNs.
منابع مشابه
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