Download Text CH 08 Cognition..

Overview of
the Adaptive Problems (Pp. 300-301)
• How do we communicate with others?
• How do we classify and categorize objects
in our world?
• How do we solve problems and reach
goals?
• How do we make decisions when
confronted with a set of alternatives?
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Communicating with Others:
Overview (Pp. 302-303)
The Structure of Language
• Structure of Language
• What sets language apart from other
communication systems: Grammar
– Language rules: Grammar
• Includes phonology, syntax, and semantics
– The hierarchical structure of language: phonemes,
morphemes, words, phrases and sentences
– The structure of sentences
– Set of rules that allow the communicator to
combine arbitrary symbols to convey meaning
– Three aspects:
• Surface structure and deep structure
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(Pp. 303-304)
Language comprehension
Language Development in Children
Language in Nonhuman Species
Is language an adaptation?
• Phononlogy: Rules for word sounds
• Syntax: Rules for combining words to make
sentences
• Semantics: Rules used to communicate meaning
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The Hierarchical Structure of
Language (Pp. 304-306)
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The Units of Language
(P. 305)
• Phonemes:
– Smallest significant sound units in speech
• Example: “ee” as in “feet”
• Morphemes:
– Smallest units of language that carry meaning
• Examples: “do,” “un”
• Word, phrases, and sentences
– Words combine to make phrases
• Example: “the interesting class” is a noun phrase
Figure 8.3
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The Structure of Sentences
Surface Structure and Deep
Structure (P. 306)
(P. 306)
• Rules of syntax determine how words combine
into phrases, and phrases into sentences
– Set of rules used to do this isn’t known
• Chomsky’s idea of how sentences work:
– Surface structure: Superficial appearance, literal
ordering of words
– Deep structure: Underlying representation of
meaning
– Producing sentences requires transformation of deep
structure into a surface structure
Figure 8.3
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Language Comprehension
(Pp. 306-307)
• How do we decide what another person is trying
to communicate?
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Language Development
(Pp. 307-308)
• Is language a product of genes or experience?
– Many researchers believe babies have some inborn
preparation for language
– Babies follow similar milestones all over the world
– Understanding speech depends on top-down as well
as bottom-up processing
– Communication depends on common knowledge
among speakers
• Babies are born producing phonemes
appropriate for many languages, but soon
narrow these down
• Pragmatic rules: How practical knowledge is
used to comprehend speaker’s intention,
produce an effective response
– Example pragmatic guidelines (Grice): Be informative,
tell the truth, be relevant, be clear
– By 3-5 weeks: Cooing
– By 4-6 months: Babbling
– By 6-18 months: Sounds become more language-like
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The Beginnings of
Communication (Pp. 308-309)
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Language in Nonhuman Species
(Pp. 310-311)
• Nonhuman animals definitely communicate
• Approximate ages for language milestones:
– But recall: not all communication is language
– 1 year: Simple words
– 2 years: Vocabulary of 200 words
• Attempts to teach chimps to speak failed
• Signs/symbols communication in chimps:
• Comprehension develops even faster; commands and
statements are understood
– Washoe: Uses about 160 signs
– Sarah: Uses plastic shapes to make “sentences”
– Kanzi: Understands speech over headphones
– 3 years: Telegraphic speech
• Grammatical knowledge fine-tuned from 3 to
about 6 or 7
• It is really language?
– Preschoolers tend to over generalize the rules
– Can they generate new combinations?
– Can they learn from other chimps?
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Is Language an Adaptation?
(P. 312)
• Why don’t most species use language, if it’s so
beneficial?
Classifying and Categorizing
(P. 313)
• Category: Class or objects that most people
agree belong together
– One view: Natural selection caused this special
ability to develop
– Another: Developed because we have large brains,
generally sophisticated thinking ability
– Being able to categorize is adaptive
• Allows us to infer properties, even if we can’t see them
directly
• Important questions about categorizing:
• Evidence for adaptation view includes special
brain regions for language, specially developed
vocal tract
– What properties about an object can make it to a
particular category?
– Do we form abstract category representations?
– Are categories organized into hierarchies?
– However: Fossil record can’t show how or when it
developed, or why
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Defining Category Membership
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Natural Categories Do Not have
Defining Features (P. 314)
(Pp. 313-314)
• Example: You know that Monopoly is an
example of the category “game,” but why?
• Defining features view: Categories defined by
features that all members share
– But: Many categories don’t have features shared by
all; boundaries are fuzzy
• Family resemblance view: Members of a
category share certain core features, but not all
members have to have all these features
Figure 8.4
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Fuzzy Category Boundaries
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Abstract Category Representations:
Prototypes (Pp. 316-317)
(P. 315)
• Prototype:
– Best or most representative member of a category
– Example: What is the best example of the category
“fruit?”
– Could categorize by comparing to prototype
• Do we really store prototypes?
Figure 8.5
– Alternative: Store all examples of the category
• Could categorize by comparing to examples (exemplars)
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Prototypes versus Exemplars
The Hierarchical Structure of
Categories (P. 318)
(P. 317)
• Most objects can be categorized in several ways
– Example: Monopoly > “board game,” “game,” “activity”
– How do we organize different categories?
• Basic-level category: Used most often, is most
useful and predictive
• Superordinate categories: More general, less
descriptive
• Subordinate-level categories: Very specific
Figure 8.6
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Category Hierarchies
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Solving Problems
(P. 318)
(Pp. 319-320)
• Two kinds of problems:
– Well-defined: Goal and starting point are clear; you
know when it’s been solved
• Researchers mainly study well-defined problems
– Ill-defined problems: Goal and starting point are
unclear; hard to tell when solution is reached
• Many real-life problems are ill-defined
– Main question: What thought processes, strategies
are used in problem-solving?
• Probably many similarities between well- and ill-defined
problems
Figure 8.7
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Guidelines to Problem Solving:
The IDEAL Problem Solver (Pp. 320-321)
• IDEAL (Bransford and Stein): Hypothetical
model of problem-solving steps
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Identifying and Defining the
Problem (Pp. 321-322)
• Problem representation: Your understanding of
what information is given and how that
information can be saved
– Identify the problem: Recognize the signs that a
problem exists
– Define (represent) problem in an efficient way: What
kind of problem is it, in your mind?
– Explore a variety of problem strategies
– Act on the problem strategy you choose
– Look back and evaluate whether the strategy was
effective,
– If not, try something new
– Must detect which information is relevant, which is not
• A problem that can arise: Functional fixedness
– Tendency to see objects and their functions in fixed
typical ways
– Hinders problem solving causing failure to identify and
define all the available “tools” to solve a problem
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The Maier Two String Problem
The Duncker Candle Problem
(P. 322)
Figure 8.8
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Exploring and Acting
Figure 8.9
Common Heuristics
(Pp. 323-324)
• Two classes of strategies:
(P. 323)
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(Pp. 324-325)
• Means-end analysis
– Algorithms: Step-by-step rules or procedures that
guarantee a solution
– Heuristics: Problem solving “rules of thumb”
• Shortcuts that are efficient, but don’t guarantee solution
• A problem that can arise: Mental set
– Find actions (means) that reduce the gap between the
current starting point and goal (end)
– Usually requires breaking down problem into sub
goals
• Working Backwards
– Tendency to rely on particular problem-solving
strategies that were successful in the past
– Start at goal state, move toward starting point
• Searching for Analogies
• When new problems can’t be solved using old
strategies > Failure
– Find a resemblance between current problem, one
solved successfully in the past
– Can be reduced by taking a break from the problem
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Framing of Decision Alternatives
(P. 328)
• Framing: Way the alternatives are structured
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Decision-Making Biases
(Pp. 328-329)
• Confirmation bias: Tendency to seek out and
use information that supports and confirms a
prior decision or belief
– Example: Is a possible course of action framed as a
way to ensure a gain, or avoid a loss?
– People tend to avoid risks when gain is emphasized,
take risks when loss is emphasized
– People avoid seeking out information that might
contradict a prior belief
• Framing can lead to choices that are irrational
from a statistical viewpoint
• Belief persistence: Tendency to cling to initial
beliefs even when confronted with disconfirming
evidence
– Example: Doctors are more likely to choose a
treatment when they see it as preventing death as
opposed to extending life
– People tend to try to find reasons why beliefs could
still be true, even with contradictory evidence
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Representativeness
Availability
(Pp. 329-330)
• When judging likelihood of something falling into
a class, compare the similarity of that thing to
the average member of that class
– Example: Which is probably a random series of coin
flips, H H H TTT or TTHTH?
(Pp. 330-331)
• Base estimates on odds of an event
occurring on ease with which examples of
the effect come to mind
– Example: Diseases that get a lot of publicity
are estimated to be more common than other
diseases
– Example: You believe it’s more likely that you
will do the dishes than your roommate
– Both are equally likely, but one is more
representative
• Mistakes that can result from representativeness:
– Ignoring the base rate
– Conjunction error
• You remember all the times you did the dishes, but
fewer of the times your roommate did them
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Anchoring-and-Adjustment
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Are Decision-making Heuristics
Valuable? (P. 331)
(P. 331)
• Research on heuristics highlights how imperfect
we are at decision making
• Judgments are influenced by starting
points, such as initial estimates
– However: Research focuses on special situations
where heuristics contradict optimal, statistically based
reasoning
– Most of the time, they are effective shortcuts
– Example: What percent of African countries
belong to the United Nations?
• “More than or less than 65?” > High estimate
• “More than or less than 10%” > Lower estimate
• Good things about heuristics:
– Often do produce good decisions in real life
– Save time and effort over optimal reasoning
strategies
– Often, we don’t have the statistical information for
optimal reasoning anyway
– Example: What is a fair price for a new car?
• Consider the sticker price first > Higher estimate
• Consider what a similar car costs used > Lower
estimate
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Solving the Adaptive Problems
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Solving the Adaptive Problems
(P. 333)
(P. 333)
• Solving Problems:
• Communicating with others:
– Humans have developed rules (grammar) for
combining sounds, words, and meanings in ways that
allow them to communicate wit others
– May be adaptation that is unique to humans
– Five main steps are involved: identify, define, explore,
act, look and learn
– Common pitfalls include functional fixedness and
mental set
• Making Decisions:
– Decisions involve choosing from among alternatives,
weighing risks
– Our choices may depend on how choices are framed
– We tend to rely on heuristics including
representativeness, availability, anchoring and
adjustment
• Classifying and categorizing:
– People rely on family resemblance to make
categorization judgments
– Categories are structured hierarchically, and people
tend to rely on the basic level most of the time
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