Spreading activation network

Exemplar and prototype theory. While a prototype is an abstract average of the members of a category, an exemplar is an actual member of a category, pulled from memory. While prototypes are economical—meaning they are more conducive to quick judgments— exemplars are less so.

Semantic networks are graph structures that encode taxonomic knowledge of objects and their properties. I show an example of such a network having these various kinds of nodes and arcs in Figure Episodic memory is the memory of every day events such as times, location geography, associated emotions, and other contextual who, what, when, where, why knowledge that can be explicitly stated or conjured.

It is the collection of past personal experiences that occurred at a particular time and place. Semantics means the meaning and interpretation of words, signs, and sentence structure. Semantics can also refer to the branch of study within linguistics that deals with language and how we understand meaning. Knowledge Representation An arc represents a two-place relation between nodes, such as the relation 'painter' between a work of art and a person.

The central reasoning mechanism in a semantic network is inheritance : a node inherits all the properties of the nodes that contain it. For instance, in Fig. There are numerous theories of how knowledge is represented and organized in the mind, including rule-based production models, distributed networks, and propositional models.

A semantic network is a method of representing knowledge as a system of connections between concepts in memory. A semantic network is a graphic notation for representing knowledge in patterns of interconnected nodes. In this way, the semantic categories described by spreading activation are a product both the actual content and of the individual experience.

For this reason, the spreading activation model is very useful for describing how the mind has responded to a semantic task, but not necessarily useful for predicting how a person will respond to any given task. Emily Daw. Please enter the following code:. According to the principle of cognitive economy, which just means that our brain is efficient, we store these properties at the highest possible node.

For example then, instead of storing can breathe at each animal's node, we store that property just at the animal node. More specific characteristics such as sings, or long legs, would be stored at lower level nodes. One pretty interesting piece of supporting evidence for this type of hierarchical organization comes from how long it takes people to verify certain statements.

In this kind of test, you say a statement, and ask people to tell you if it's true or not. As you can imagine, people verify a canary is a canary pretty quickly. It takes them a little longer to verify a canary is a bird, and even longer to verify that a canary is an animal. So this is some support that we store things in a hierarchical manner, because the longer it takes us to verify a connection between two nodes, then the longer those links are, or the more nodes we have to go through to make that link.

However, this isn't true for all types of animals, or even all types of categories. For example, people tend to verify that a pig is an animal faster than a pig is a mammal. Because of this issue and some other problems, Collins and Loftus proposed a modified version of the semantic network.

Register Don't have an account? Spreading activation. View source. History Talk 0. See also Cognitive contiguity References John R.