Cognitive Processes PSY 334 Chapter 5 – Meaning-Based Knowledge Representation July 24, 2003

Propositional Representations  Notation – a method for describing the meaning that remains once details have been abstracted away.  Propositional representation – uses concepts from logic and linguistics to describe meaning.  Proposition – the smallest unit of knowledge that can be judged as true or false.

Propositional Analysis  A complex sentence consists of smaller units of meaning (propositions).  If any of the propositions are untrue, the entire sentence cannot be true.  The meaning of primitive assertions is preserved, but not the exact wording.

Kintsch’s Notation Each proposition is a list containing a relation plus arguments: (relation, arguments)  Relation – organizes the arguments. Verbs, adjectives, other relational terms.  Arguments – particular times, places, people, objects. Nouns  Relations connect arguments.

Psychological Reality  Psychological reality -- do propositions really exist mentally?  Bransford & Franks: Presented 12 sentences with the same 2 sets of 4 propositions. Tested on 3 kinds of sentences. Old (previously viewed), new (containing same propositions), noncase (new and containing different propositions).  Able to identify noncase, but not old/new

Propositional Networks  Propositional network – another way of representing propositions (the structure of meaning).  Nodes – the propositions, including relations and arguments.  Links – labeled arrows connecting the nodes.  Spatial location of nodes is arbitrary.  Can show hierarchies of meaning.

Associations Between Ideas  Weisberg – demonstrated that ideas are associated in the ways shown in a propositional network. Subjects memorized sentences. Given a word from the sentence, subjects were asked to say the first word that came to mind. Subjects cued with “slow” said “children” and almost never “bread”.

Conceptual Knowledge  Concept -- an abstraction formed from multiple experiences. Propositions – eliminate perceptual details but keep relationships among elements.  Categories – eliminate perceptual details but keep general properties of a class of experiences. Used to make predictions. Two kinds: semantic networks, schemas

Semantic Networks  Quillian – information about categories stored in a network hierarchy. Nodes are categories. Isa links related categories to each other. Nodes have properties associated with them.  Properties of higher level nodes are also true of lower level nodes linked to them. Categories are used to make inferences.

Psychological Reality of Networks  Collins & Quillian – asked subjects to judge the truth value of sentences: Canaries can sing – 1310 ms Canaries have feathers – 1380 ms Canaries have skin – 1470 ms  Frequently used facts also verified faster, so stored with node: Apples are eaten Apples have dark seeds

Schemas  Schema – stores specific knowledge about a category, not just properties: Uses a slot structure mixing propositional and perceptual information. Slots specify default values for what is generally or typically true.  Isa statement makes a schema part of a generalization hierarchy.  Part hierarchy.

Psychological Reality of Schemas  Brewer & Treyens – subjects left in a room for 35 sec, then asked to list what they saw there: Good recall for items in schema False recall for items typically in schema but missing from this room. 29/30 recalled chair, desk; 8 recalled skull 9 recalled books when there were none

Degrees of Category Membership  Members of categories can vary depending on whether their features satisfy schema constraints: Gradation from least typical to most typical.  Rosch – rated typicality of birds from 1-7: Robin = 1.1 Chicken = 3.8.  Faster judgments of pictures of typical items, higher sentence-frame ratings.

Disagreements at Category Boundaries  McCloskey & Glucksberg – subjects disagree about whether atypical items belong in a category: 30/30 apple is a fruit, chicken is not a fruit 16/30 pumpkin is a fruit Subjects change their minds when tested later.  Labov – boundaries for cups and bowls change with context.

Event Concepts (Scripts)  Schank & Abelson – stereotypic sequences of actions called scripts.  Bower, Black & Turner – script for going to a restaurant.  Scripts affect memory for stories: Story elements included in script well remembered, atypical elements not recalled, false recognition of script items. Items out of order put back in typical order.

Two Theories  What happens mentally when we categorize? Two theories are being debated.  Abstraction theory -- we abstract and store the general properties of instances. Prototype theory.  Instance theory -- we store the multiple instances themselves and then compare average distances among them.

Neural Nets for Learning Schemas  Gluck & Bower – designed a neural net that abstracts central tendencies without storing instances. Patients with four symptoms classified into two hypothetical diseases. One disease 3 times more frequent than the other. Error correction changes the strength of associations in the network (delta rule).  Model predicted subject decisions well.

Evidence From Neuroscience  People with temporal lobe deficits selectively impaired in recognizing natural categories but not artifacts (tools)  People with frontoparietal lesions unaffected for biological categories but cannot recognize artifacts (tools).  Artifacts may be organized by what we do with them whereas biological categories are identified by shape.

Bartlett’s War of the Ghosts  Demo