problem solving Flashcards
problem solving
multi step process to shift your current problem state to a goal state
higher order state
- math, social, everything - super broad
problem solving cycle
- define problem
- brainstorm
- solution
- try solution
- review results
what are the three characteristics of problem solving
cyclical - enact steps that occur in a loop
recursive- repeat the cycle for as many times as necessary to find a solution
applicable - apply successful cycles (solutions) to new problems
types of problems
well defined problems
- requirements are unambiguous
- all information is present
- applying rules or algorithms
- puzzles
ill defined problems
- how to overcome problem/goal is ambiguous
- requires added information
- situational
- my laptop is broken
goal directedness
characteristic of well defined problems
problems with a defined goal state and set task constraints such that there are clear steps - ex. sudoku puzzle
social solving
a form of ill defined problem solving
anagram study and cognitive load
tested people for ill defined - no constraints and well defined anagrams -constraints (word jumble)
greater activity in the right lateral prefrontal cortex for ill defined anagrams
solving ill defined problems carries a greater ‘cognitive load’ (amount of information held in mind at one time
Moravec’s paradox
“everything that is easy is hard, and everything thats hard is easy”
AI can solve well defined problems well, but not ill defined problems and simple skills
it is often defined by the use of algorithms, deep neural networks, that work well with certainty but not with uncertainty
problem state
a representation that includes
- initial and goals states
- intermediate paths and operators: actions to change between states
- task constraints
The tower of Hanoi
example of a problem state
given pegs and disks and told to move 3 discs from peg A to C so they are in the same initial order
constraints:
- as few moves as possible
- no disc can lie on top of a smaller one
- only one disc can be moved at a time
a brute force approach
systematic algotrithm that represents all the possible steps from the problems to goal state
blind search, guaranteed to find a solution, but inefficient
can lead to combinatorial explosion
combinatorial explosion
computing too many alternatives
Heuristics
strategies to select moves in a problem space
helps avoid combinatorial explosion
- two examples
- hill climbing and means end
hill climbing strategy
difference reduction strategy
select the operation that brings you closer to the goal without examining the whole problem space - just moving up towards goal
can lead to a false outcome, a ‘local maxima’ that is mistaken as the final goal
doesn’t work for problems that require you to move away from a goal in order to solve it
means ends strategy
moving more dynamically through problem state - more flexible than hill climbing
what ‘means’ do i have to make the current state look like the goal state i want to be in?
identifying sub problems to complete the goal
includes forward and backwards movements and constantly evaluating the difference between current and goal states
expertise and problem solving
experts are more familiar with certain information and so they represent a problem differently than non experts
tend to take a more holistic or global view
analogical problem solving
making comparisons between two situations - applying the solution from one of the situations to the other situation
however, people aren’t good at using analogies unless they are reminded/given a hint
without the hint, a person must look beyond surface details, and consider the general structure (the gist)
target and source analogical problem solving
target: problem you are trying to solve
source: past situation/example you are applying
when does analogical problem solving have the best success
when a source and target share surface and structure
THe Einstellung effect
the bias to use familiar methods to solve a problem
can result in an inability to seek and use a better method to solve a given problem
leads to rigid thinking and blocks in problem solving
two results of einstellung effect
functional fixedness and mental fixedness
functional fixedness
the inability to see beyond the most common use of a particular object
“fixed” on the function of an object you know
mental fixedness
responding with previously learned rule sequences even when they are inappropriate or less productive
the tendency to respond inflexibly to a particular type of problem and not alter your response
classic test of functional fixedness
maier’s two string problem
- person in a room two strings, have to bring together, but strings are too far apart to touch
- paint cans, other stuff, stc
ex. can tie paint brush or can to one string and swing it to touch the other while u hold
in 10 min only 39% of ps can find solution
if given hint (told to swing arms on a break) found answer quicker
