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problem solving cycle
- identify the problem2) define the problem3) construct a problem solving strategy4) organize information5) allocation of resources6) monitor solving7) evaluate solution TERM 2
goal state
DEFINITION 2 what the solution would look like when you have succeeded TERM 3
operators
DEFINITION 3 rules about what 'moves' or actions can be made TERM 4
in the real world defining ___ may be difficult
DEFINITION 4 the goal state and the operators TERM 5
if you attend to the wrong information you will
not __
DEFINITION 5 solve problems correctly(also demonstrates working memory capacity limits)
method of solution often depends on ___
method of representation TERM 7
incremental problems
DEFINITION 7 straight forward stepwise manner.prior knowledge is helpful(ex. long math problems) TERM 8
incubation
DEFINITION 8 start a problem, do something else, and the percentage of people solving the problem jumped up a lot TERM 9
Gestalt position on
incubation:
DEFINITION 9 unconscious processing produces advantage (work on problem in the background) TERM 10
Silveria tape recorded subjects doing think-
aloud protocol. ___
DEFINITION 10 they picked up where they left off (no progress during incubation)
insight problems
prior knowledge hinders performance (get stuck). Need to restructure your representation of the problem TERM 17
organization of information
DEFINITION 17 organize available information in way that enables you to implement your strategy TERM 18
functional fixedness
DEFINITION 18 restricting use of an object to its familiar functions TERM 19
types of strategies:
DEFINITION 19 algorithmsheuristics TERM 20
algorithms
DEFINITION 20 guarantee of success if applied appropriately-requires well defined operations and goal state-require brute processing strength that people may not have (can be inefficient for people)-good for computers
heuristics
no guarantee of successshort cuts and basic strategies that usually work-for fewer demands on processing resources than algorithms TERM 22
algorithms: dumb/simple
search
DEFINITION 22 randomly choose an operator, apply it. if the goal has not been met try a different operatortrial and errorguaranteed to solve well divined problemvery inefficientex. finding the right key by trying all of them TERM 23
algorithm: searching the problem space
DEFINITION 23 ex. tower of Hanoioperations: can move only one disk at a timecan move disk only when no disks are on top of itcannot put a larger disk on top of a smaller disk TERM 24
heuristic method: hill climbing
strategy
DEFINITION 24 (difference reduction)every step takes you cooer to your goalno need to think through the whole problem TERM 25
heuristic method: means-end
analysis
DEFINITION 25 also tries to eliminate differences between current state and goal statebut identifies subgoals and works towards the subgoal. Once achieved, select the next subgoal and work towards itex. getting a high degree
differences between puzzle problems and
real-world problems: puzzles
unfamiliarinvolve little prior knowledgeall necessary infer is present in the problem staterequirements are unambiguous TERM 32
how experts solve
problems:
DEFINITION 32 experts focus on structural rather than surface factors, novices do the oppositeexperts spend more time initially analyzing problemexperts are not better than novices when given problems outside of their fieldexperts less likely to be open to new ways of looking at problems TERM 33
means-end analysis
DEFINITION 33 there are three missionaries and three cannibals on one side of river and they need to get to the other sidethe boat can only carry two people at a timethere can never by more cannibals than missionaries in one location (or they will eat them) TERM 34
salient differences between problems and
real-world: real-world
DEFINITION 34 familiarrequire some prior knowledgenecessary information is not present
