1. Psychology of Thinking: Embedding Artifice in Nature

2. 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

3. 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?

4. 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

5. 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”

6. 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

7. 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

8. 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

9. 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 occurs in a combinations of verbal, mathematical, and diagramatic reasoning Potential issues with Simon’s interpretation – Simple problems -> simple solutions – What about perception?

10. 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?)

11. What does it mean to know? Searle’s Chinese Room

12. 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?