PSYC 325 Lecture Notes - Lecture 9: Electronic Component, Artificial Neural Network, Fokker E.Ii
1 Oct 2016
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Generalization and discrimination learning: generalization: transfer of past learning to new situations, problems, and stimuli, perception of differences between similar stimuli will be reflected in b. If 2 s are perceived as being highly similar, there will be sig generalization between them. Discrete component vs distributed representations: discrete-component representation, stimuli are categorical, with unique mental input-nodes, no response generalization, 2 nodes and 1 weight. One layer network links from various cues to the possible o. Each presentation of trial was modulated by activating the corresponding input node for each stimulus cue while being multiplied by the associative weight of each link d. iii. When activation from a given input node reaches an output node, added to the incoming activations (multiplied) by weights) of all the other activated stimulus cues on the trial. P learn to minimize the difference between what actually happens and their expectation of that o d. iv. d. v: limitation e. i. e. ii.
