COMPLEX LEARNING TASKSChapter 12

Concept Learning Concept

A symbol that represents a class of objects or events with common properties.

For example, think of an airplane: Have fixed wings Are heavier than air Are driven by a screw propeller or high velocity

rearward jet Are supported by the dynamic reactions of the

air against the wings These concepts allow us to easily identify

these objects as airplanes.

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Concept learning significantly enhances our ability to effectively interact with the environment.

Rather than separately labeling and categorizing each new event or object, we incorporate it into our existing concepts.

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Well Defined Concepts Attribute

Any feature of an object or event that varies from one instance to another.

Rule A rule defines the objects or events that are

examples of a particular concept. Types of Rules

Affirmative rule A rule that specifies that a particular attribute defines a

concept. Negative rule

A concept is defined by the rule that any object or event having a certain attribute is not a member of the concept.

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Studying Concept Learning in Humans Smoke (1933) conducted studies

examining concept learning in humans. He presented subjects with a large number

of figures that differed in shape, size, number, and location of their dots.

Subjects’ task was to learn the concept of DAX, which consisted of a circle with one dot inside and another dot outside.

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Conjunctive rule The simultaneous presence of two or more attributes that

define a concept. Disjunctive rule

When the concept is defined by the rule that the concept can possess either or both of the two common attributes.

Not all examples of a concept necessarily have all the attributes characteristic of that concept.

There are degrees to which particular items fit a concept.

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Fuzzy Concepts Family resemblance

The degree to which a member of a concept exemplifies the concept.

PrototypeObject with the greatest number of attributes

that are characteristic of the concept.Chair is the most typical prototype of

furniture.

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Who’s sexier?

A German Shepherd may fit the concept of dog more than a poodle.

The more an object or event differs from the prototype, the more difficult it is to identify it as an example of the concept.

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Multiple Concepts Two objects or events may share certain

attributes but not be examples of the same concept. Although a robin and a bat both have wings, a

robin is a bird and a bat is a mammal. We do not always know the boundaries that

define a concept.

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Study of Concept Learning in Animals

Concept learning involves identification of the properties that characterize a concept as well as those that do not.

Herrnstein et al. (1976) found that pigeons demonstrated concept learning. Trick is to use a large number of very different

examples D’Amato and Van Sant (1988) found that monkeys

could learn the concept of humans. Vonk and MacDonald found that a female gorilla

could learn to discriminate between primate and non primate animals.

Animals can also learn the concepts of same and different.

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Cook & Blaisdell (1996)13

Theories of Concept Learning Hull (1920) envisioned concept learning as

a form of discrimination learning. Said that concepts have both relevant and

irrelevant attributes. As a result of reinforcement, response

strength increases to the attributes characteristic of the concept.

Same/Different judgements require an abstract code or rule, so the theory fails here.

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Abstract Concepts Bruner, Goodnow, and Austin (1956)

suggested that a concept is learned by testing hypotheses about the correct solution. If the first hypothesis is correct, the individual

has learned the concept. If it is incorrect, another hypothesis will be

generated and tested, and this will be repeated until the correct solution is discovered.

Research by Levine (1966) suggests that individuals do engage in hypothesis testing of concepts.

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Two Ways of Knowing However, a concept can be learned via

associative learning or hypothesis testing, which are not necessarily mutually exclusive.A concept can be learned using either

method, but a concept is learned best when both methods are employed.

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TOM Concept or Discrimination?• Theory of Mind: Understanding that others

have mental processes that may differ from one’s own.

EmotionsKnowledgeVisual Perspective

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Knowledge Attribution

Povinelli (1991)

Knower – sees food being hidden Guesser – outside of room

Stage 1: As aboveStage 2: Knower wears hatStage 3: Guesser stays in room with a

bagged head

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Chimpanzees(Great Apes)

Rhesus Monkeys(New World)

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Alternative

Did chimps discriminate between the two situations based on subtle differences in how the “guesser” and “knower” acted?

Maybe they choose the one with eyes open during hiding?

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“Begging Experiment”

Povinelli (1999)

Beg from “seeing” vs. “nonseeing”

Front vs. Back – Yes Pail Beside vs. Over Head - No Averted Eyes vs. Over Shoulder Look –

No Blindfold Mouth vs. Blindfold Eyes - No

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“Chimps Fail Begging Experiment”23

“Elephants Pass Begging Experiment”

However, this doesn’t imply elephants can “mind-read”

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Mark Test

Gallup’s Mark Test (Great Apes)

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The Nature of the Problem Problem

A situation in which a person is motivated to reach a goal, but some obstacle(s) block the attainment of the goal.

Thorndike (1898) proposed that animals and people solve problems by trial and error.

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Insight or Trial and error? Kohler (1925) suggested a different view

of problem solvingSays that an animal internally or mentally

explores the problem before exhibiting a specific response.

The exploration involves considering and rejecting possible solutions and finally developing insight as to the correct solution.

But…..only Chimps with certain past experiences solved the banana problem

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Insight: What is it? Insight

A sudden realization of how to solve a problem.Kohler found that once the subjects solved the

problem, they were able to quickly solve other similar problems.

Initial stateThe starting point of a problem.

Goal stateThe desired endpoint of a problem.

Two additional processes:Identify the operations that solve the problem.Restrictions limit what you can do.

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Well or Ill? Well-defined problem

A problem with clear initial and goal states. Ill-defined problem

A problem with no clear starting or end point.

Creating a set of manageable subproblems provides the structure for converting an ill-defined problem into a well-defined one.

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A Strategy for Solving Problems After the problem has been defined, the

next step is to develop a plan of attack. There are two major strategies—

algorithms and heuristics—that can be used to solve problems.

Algorithm A precise set of rules to solve a particular

problem. Heuristic

A “best guess” solution to problem solving.

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Working backward heuristicA technique for finding the solution to a

problem by starting with the end point and working back to the start point.

Is often used in mathematical and other formal systems of analysis.

Means-end analysisBreaking a particular problem into a series

of solvable subproblems.

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MeansEnds Analysis?

Learning a) allows the bird to solve b)

Consequences of Past Experience Functional fixedness

Difficulty recognizing novel uses for an object.

Prior experience using an object to solve one problem makes it difficult to recognize that the same object can be used in a different manner to solve another problem.

Reflects rigidity that can impair problem solving; however there are ways to overcome functional fixedness.

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Mental SetsThe tendency to use an established method

for solving problems.Sets may blind people to fresh ways of

exploring problems, which is unproductive when other solutions are more efficient.

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