Psychology of Thinking: Embedding Artifice in Nature

Perceived Complexity

• Many things that appear complex are result of simple mechanism acting on a complex environment

• Consider the path of ant on seashore or skier on mountain slope– Path might be mistaken

for a student’s path through problem/solution space when solving a complex problem

• Complexity largely due to not being able to anticipate obstacles

Perceived Complexity

• “An ant, viewed as a behaving system, is quite simple.”

• Controversial hypothesis?– “Human beings [minus emotions

and memories], viewed as behaving systems, are quite simple.”

• Do you believe Simon?• Why does Simon believe this? • How does it relate to theory of computing?

Understanding Thinking

• Examine results from cognitive psychology– What do they tell us about capabilities?– What do they tell us about limits?

• Look at– Problem solving– Concept attainment– Memory skills– Natural language processing

Problem Solving as Search

• Generalizing search (e.g. cryptoarithmetic problems)– Brute force solutions – Pruning tree based on

contradictions– Algebraic solution based on design constraints

• “the more sophisticated the search strategy, the less search was required”

Problem Solving as Search

• My take: the more domain knowledge applied, the less search is required– Is search the right word?– Generate and test vs. compute value

• People change strategies – is this just searching for a search strategy?

• Lesson: watching people solve problems can provide information about cognitive processes

Concept Attainment

• Example with cards– Determining which cards show things in a class of items

and which are not in the class– Experiments show

• People do not always discover strategies that could be taught• People do not have sufficient memory unless process is slowed

down

• 7 +/- 2 elements in short-term memory

• 5-10 seconds to move chunk to long-term

Patterns in Experimental Results

• Problem in reporting experimental results in variety of metrics– # of trials, # of errors, time to criterion

• Learn unrelated nonsense syllables (Task A)– 10-15 seconds each

• Learn unrelated words or related nonsense syllables– 1/3 time of Task A

• Learn continuous prose– 1/10 time of Task A

• Modeling experience with EPAM– Approximately predicts times found in studies

• Simon suggests 2 chunks of short-term memory– Only 7 to 10 if no interruptions to task

Organization of Memory• Recall of randomized characters show chunking (at multiple

levels)– Three to four at each level?– Simon hypothesizes list structure (LISP)

• Recall of chess boards– All are slow on randomly placed chess

pieces– Experts faster on boards that made

sense

• In practice, problem solving occursin a combinations of verbal, mathematical, and diagramatic reasoning

• Potential issues with Simon’s interpretation– Simple problems -> simple solutions– What about perception?

Natural Language Processing

• Connection between transformational linguistics and information-processing psychology

• I saw the man on the hill with the telescope– SAW ((I, WITH (telescope)),

(man, ON (hill)))• Only the expressible

thinkable? (vice versa?)

What does it mean to know?

• Searle’s Chinese Room

Lessons / Summary

• “the system is basically serial in its operation”– Do you agree?– Where is this true? Where might it be false?

• Experimental work can provide insight into cognitive processes

• “we should not expect it [cognition] to become essentially more complex”– Why not? Should we expect for it to remain

simple?