Machine Learning and Vision
Connectionism and the Philosophy of Psychology
Human cognition is soft. It is too flexible, too rich, and too open-ended to be captured by hard (precise, exceptionless) rules of the sort that can constitute a computer program. In Connectionism and the Philosophy of Psychology, Horgan and Tienson articulate and defend a new view of cognition. In place of the classical paradigm that take the mind to be a computer (or a group of linked computers), they propose that the mind is best understood as a dynamical system realized in a neural network.
Although Horgan and Tienson assert that cognition cannot be understood in classical terms of the algorithm-governed manipulation of symbols, they don't abandon syntax. Instead, they insist that human cognition is symbolic, and that cognitive processes are sensitive to the structure of symbols in the brain: the very richness of cognition requires a system of mental representations within which there are syntactically complex symbols and structure-sensitive processing.
However, syntactic constituents need not be parts of complex representations, and structure sensitive processes need not conform to algorithms. Cognition requires a language of thought, but a language of thought implicated in processes that are not governed by hard rules. Instead, symbols are generated and transformed in response to interacting cognitive forces, which are determined by multiple, simultaneous, (robustly) soft constraints. Thus, cognitive processes conform to soft (ceteris paribus) laws, rather than to hard laws. Cognitive forces are subserved by, but not identical with, physical forces in a network; the organization and the interaction of cognitive forces are best understood in terms of the mathematical theory of dynamical systems.
The concluding chapter elaborates the authors' proposed dynamical cognition framework.
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