PSYC 305 Chapter Notes - Chapter 8: Causal Structure, Causal Inference, Dishabituation
Document Summary
Natural causality: physical causal events in which the generative processes are relatively apparent (ex. Arbitrary causality: a relationship in which the generative processes of the causal interaction are not readily apparent (ex. ***mechanisms that underlie the two types may differ. Humans and animals use associative mechanisms to learn about causal relations: therefore causal learning is a by-product of associative learning. **shows that some conditioning tasks may actually imply causal learning that cannot be explained through associations. Idea: people understand causal structures in the world in a manner that can be modelled by causal. Bayes nets: causal bayes nets: causal structures of the world are depicted with graphs in which letters denote events and the arrows denote causal relationships. Common cause model: event a can result in both b and c, but b and c do not have a causal relationship. Causal chain model: event a causes b which in turn causes c but a does not directly cause c.
