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Varieties of Learning Structural descriptions and instances Scenarios and locations; eating in a fast food restaurant Perceptual and semantic representations.

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Presentation on theme: "Varieties of Learning Structural descriptions and instances Scenarios and locations; eating in a fast food restaurant Perceptual and semantic representations."— Presentation transcript:

1 Varieties of Learning Structural descriptions and instances Scenarios and locations; eating in a fast food restaurant Perceptual and semantic representations What McDonald’s looks like and why you go there; sentences and their meanings Wholes and Parts What McDonald’s looks like and what the golden arches looks like.

2 Part-Whole Recognition Procedure 48 study items presented whistle-BALL recognition tests for individual words RACKET NET BALL recognition test for pair whistle-BALL pretty-WET cave-BLUE Results Recognition of single words independent of pair Conclusion More than one representation of study item may be independently encoded in memory

3 Varieties of Learning Structural descriptions and instances Scenarios and locations; eating in a fast food restaurant Perceptual and semantic representations What McDonald’s looks like and why you go there; sentences and their meanings Wholes and Parts What McDonald’s looks like and what the golden arches look like.

4 Categorization

5 Definition The Role of Perception in Categorization The Role of Semantics in Categorization

6 Definitions When an infant kicks to move a mobile we may call the mobile: The target of the kicking response The stimulus of the kicking response The cue for the kicking response The moving mobile is the consequence of the act of kicking.

7 Generalization When the same action has produced the same consequence in response to more than one target, the probability of a novel object activating a representation of the action and its consequence is a function of its similarity to all previous targets of the action. An infant who has kicked to move two different mobiles will kick to move a third mobile that is a composite of the previous two.

8 Learning a Generalization The more targets of an action, the more likely that a novel input will match the target set sufficiently to elicit the action. Hence, when an action has produced the same consequence for more than one target, the result is a bootstrap effect between the number of targets associated with the action and the probability of a new target eliciting the action. The greater the variety of targets to which an action has been successfully directed (i.e., produced the same desired response), the greater the variety of targets that will elicit the action. Once an infant learns that kicking can move two different mobiles, the infant will kick to any mobile.

9 Categorization When representations of different items become associated with the same consequence of the same action, the items are said to be instances of the same category. In explicit categorization, in addition to other possibly actions uniting the instances, the action of naming produces the same result, the verbal category label, for the instances. All colors are called colors.

10 Categorization Definition Category instances are different targets of the same action. The Role of Perception in Categorization The Role of Semantics in Categorization

11 Categorization Definition The Role of Perception in Categorization Natural Categories Artificial Categories The Role of Semantics in Categorization

12 Categorization Definition The Role of Perception in Categorization Natural Categories When instances automatically match features in each other’s representations as the result of perceptual organization Hence, these categories are determined by how the perceptual system organizes the inputs. For example, color and shape categories (Heider, 1972) Artificial Categories The Role of Semantics in Categorization

13 Categorization Definition The Role of Perception in Categorization Natural Categories When instances automatically match features in each other’s representations as the result of perceptual organization As a result of perceptual organization, some features are more salient than others. Salient features make categorization easy so that categories may be formed by simple observation, even without instructions to do so (Fried and Holyoak, 1984). Examples: Color categories, “chair,” “table,” “bird.” Artificial Categories The Role of Semantics in Categorization

14 Natural Rectangle Categories Higher than wider versus wider than higher. May be sorted without feedback.

15 Salient Features The salient features of a representation are those features that are weighted most heavily by the perceptual system in determining the similarity between two representations.

16 Nose is more salient feature than ears; so it determines category

17 Categorization Definition The Role of Perception in Categorization Natural Categories Basic level categories are natural categories that exist in the perceptual system and the world. Examples: “chair,” “table,” “bird.” Artificial Categories The Role of Semantics in Categorization

18 Basic Level Categories Are broadest category at which members have many perceptual features in common. Have similar shapes. Are among the first categories learned.

19 Picture Naming of Basic Categories Pictures of objects are named by the basic category term 99% of the time. However, experts are different. People with expertise (detailed knowledge of differences among category members) use the subordinate term to name pictures of objects in their area of expertise. Same as others for categories not in area of expertise.

20 Categorization Definition The Role of Perception in Categorization Natural Categories Artificial Categories The instances of a category do not automatically match features in each other’s representations as the result of perceptual organization. Hence they are not formed just by observation. Rules, descriptions, or feedback must be given to learner for category concept to be formed. Nevertheless, perceptual features are used to recognize instances of artificial categories The Role of Semantics in Categorization

21 An Artificial Category Size greater than tilt versus tilt greater than size. Requires feedback for learning. Rule may not be capable of articulation by learner.

22 Categorization Definition The Role of Perception in Categorization The Role of Semantics in Categorization In addition to perceptual matching, an observer extracts and labels perceptual features for a technical definition containing defining features A birds lay eggs and all birds and only birds have feathers

23 Categorization Definition The Role of Perception in Categorization The Role of Semantics in Categorization Verbal labeling of perceptual features makes category definitions possible. Once sufficient language is learned, verbal definition plays a role in category learning

24 Gelman & Markman (1986) study  3-4 years of age  Bird (flamingo) gives baby mashed food; Bat gives milk.  What does (black)bird do?  68% say mashed food

25 Categorization Definition The Role of Perception in Categorization The Role of Semantics in Categorization Verbal labeling of perceptual features makes category definitions possible. Once sufficient language is learned, verbal definition plays a role in category learning Categories may also be defined by nonperceptual features.

26 Types of Categories Perceptual. Most objects (rocks, animals, etc.) Functional. Tools, furniture, weapon, occupational, etc. Kinship. Mother, uncle, etc. Abstract. Justice, etc. Categories defined by enumeration. 26 letters of the alphabet.

27 Categorization The Role of Semantics in Categorization Verbal labeling of perceptual features makes category definitions possible. Once sufficient language is learned, verbal definition plays a role in category learning Categories may also be defined by nonperceptual features. Categories have internal structure determined by the similarity among instances. Knowledge of a category includes: Knowledge of typical instances Knowledge of atypical instances Frequency of occurrence.

28 Typical and Atypical Members There is an asymmetry in comparing the similarity of typical and atypical instances: ___ is virtually a ___. Try pink versus red. Definition of typicality for multi-feature instance representations Instance typicality is a function of the number of other instance representations it is similar to. Similarity may be determined by both category relevant and category irrelevant features. Typical instances also called focal and prototypical instances.

29 Categorization The Role of Semantics in Categorization Verbal labeling of perceptual features makes category definitions possible. Once sufficient language is learned, verbal definition plays a role in category learning Categories may also be defined by nonperceptual features. Categories have internal structure determined by the similarity among instances. Categories are hierarchically organized and share instances

30 Verbal categorization makes hierarchical organization possible Category labels may be treated as instances and associated with more general category labels. Dogs, cats, etc. are all animals All mature learning depends on prior knowledge. Novel items are associated with existing category labels on the basis of similarity to familiar instances. These are the semantic associations.

31 Semantic Categorization and Learning Semantic categorization is the basis of declarative memory As a result, additional representations are activated when a perceptual representation is constructed. Semantic categorization also facilitates procedural memory Category nodes in structural descriptions make it possible to automatically construct an infinite number of perceptual representations


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