2002 年 20 巻 2 号 p. 169-174
Connectionism is an approach to understanding the mechanisms of human cognition using simulated networks of neuron-like processing units. In this article, I report on recent progress in connectionist models that simulate empirical data relating to human memory processes, these being AB-AC list learning, word naming, understanding word meanings, and sentence understanding. I also summarize the advantages and disadvantages of these connectionist models. I argue that connectionist computer simulation offers significant benefits for today's psychological researches.