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David Everett Rumelhart (June 12, 1942 – March 13, 2011) [1] was an American psychologist who made many contributions to the formal analysis of human cognition, working primarily within the frameworks of mathematical psychology, symbolic artificial intelligence, and parallel distributed processing.
In psychology, parallel processing is the ability of the brain to simultaneously process incoming stimuli of differing quality. [1] Parallel processing is associated with the visual system in that the brain divides what it sees into four components: color , motion , shape , and depth .
TRACE was created during the formative period of connectionism, and was included as a chapter in Parallel Distributed Processing: Explorations in the Microstructures of Cognition. [3] The researchers found that certain problems regarding speech perception could be conceptualized in terms of a connectionist interactive activation model.
The second wave blossomed in the late 1980s, following a 1987 book about Parallel Distributed Processing by James L. McClelland, David E. Rumelhart et al., which introduced a couple of improvements to the simple perceptron idea, such as intermediate processors (now known as "hidden layers") alongside input and output units, and used a sigmoid ...
A further distinction is whether the architecture is centralized, with a neural correlate of a processor at its core, or decentralized (distributed). Decentralization has become popular under the name of parallel distributed processing in mid-1980s and connectionism, a prime example being the neural network.
Parallel constraint satisfaction processes can be applied to three broad areas in social psychology: [1] Impression formation and causal attribution; Cognitive consistency; Goal-directed behavior. This approach revealed that some phenomena that seem unexpected or counterintuitive are in actuality due to the normal functioning of the cognitive ...
Lucy Popova's 'The Extended Parallel Process Model: Illuminating the Gaps in Research', is an extensive review on the theoretical and empirical applications of the EPPM. [11] Popova discovered that the strong theoretical foundations has some inconsistencies in a few of its operational definitions. A systematic review of existing literature on ...
He is best known for his work on statistical learning and Parallel Distributed Processing, applying connectionist models (or neural networks) to explain cognitive phenomena such as spoken word recognition and visual word recognition. McClelland is to a large extent responsible for the large increase in scientific interest in connectionism in ...