A connectionist model assumes that on each learning trial,
A) causal power is replaced with associative strength.
B) the strength of a connection between nodes representing features and categories can be updated by same laws that govern classical conditioning.
C) once learning has occurred, causal power takes over to determine the final output.
D) when multiple features are activated they will produce blocking, potentiation, inhibition, and other standard learning phenomena.

Question

Quizplus · Accepted Answer

Connectionist models, also known as neural network models, assume that learning involves updating the strength of connections between nodes (representing features and categories) in a way that mirrors the principles of classical conditioning. This involves adjusting the weights of these connections based on the learning input, which allows the model to make predictions or categorizations based on the input it receives.

A Connectionist Model Assumes That on Each Learning Trial