Modeling in Neural Networks
Neural network models of cognition have provided the necessary framework to integrate the empirical research done on cognitive dissonance and attitudes into one model of explanation of attitude formation and change.
Various neural network models have been developed to predict how cognitive dissonance will influence an individual's attitude and behavior. These include:
- Parallel Constraint Satisfaction Processes
- The Meta-Cognitive ModelMeta-Cognitive Model (MCM) of attitudes
- Adaptive connectionist model of cognitive dissonance
- Attitudes as constraint satisfaction model
Read more about this topic: Cognitive Dissonance
Famous quotes containing the words modeling and/or networks:
“The computer takes up where psychoanalysis left off. It takes the ideas of a decentered self and makes it more concrete by modeling mind as a multiprocessing machine.”
—Sherry Turkle (b. 1948)
“The great networks are there to prove that ideas can be canned like spaghetti. If everything ends up by tasting like everything else, is that not the evidence that it has been properly cooked?”
—Frederic Raphael (b. 1931)