Problem Solving Flashcards

1
Q

How do we solve problems?

A

Define, shape, simplify the problem

Generate possible solutions, evaluate them

Implement best solution… verify it!

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2
Q

Ways to solve problems?

A

Guesswork (luck!)
•Intuition, hunches
•Elimination
•Pragmatics (logical reasoning)
•Semantics (interpreting underlying meaning)
•Abstract thinking
•Mental flexibility
•Creativity & insight

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3
Q

Problem solving characteristics?

A

Problems must have a goal (goal directed behaviour)
- Daydreaming about achieving “the good life” is not problem solving

Sequential steps
- Must involve multiple operations

Simple recall is not problem solving

If I lock my keys in my car, or lose them, that’s a problem
- Goal = retrieve my keys
- Breaking-in causes (counter-intuitive) damage, searching requires multiple (time-consuming) steps (or “operations”)

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4
Q

What is a goal?

A

The ultimate destination, solution, or state of a problem

May need problem “decomposition” (breaking down into necessary steps)

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5
Q

Whats an ill-defined goal?

A

No explicit goal

E.g., “I need to buy my boss an impressive gift”

Several different results could satisfy the goal of “impressive gift”

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6
Q

What are operators?

A

Discrete moves, functions or steps towards goal

E.g., recall, logical reasoning, mathematics, motor movements

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7
Q

What are legal and illegal operators?

A

Permissible given the problem constraints (rules)

Not permissible given problem constraints

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8
Q

What are heuristic approaches?

A

Mental short cuts to help us reach a solution with less time and cognitive effort – this is their weakness

Trial and error, educated guesses, intuition

No guarantee these quick solutions are the best solutions – often they’re not

We use heuristics all the time
- e.g., deciding on the best deals, choosing your next book, considering the least congested route through town, etc.

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9
Q

What are working backwards heuristics?

A

A heuristic in which you solve by working backwards from the goal state

E.g., Dan gave Isobel 4 sweets, Jane 3 sweets and Steve 6 sweets. Dan now only has 4 sweets left.
•How many sweets did Dan start with?

Handy for mazes, and maths formulae:
•e.g., SE of mean = SD/SQRT of sample size
•So, if you need the SD but only have SE, reverse the formula:
•SD = SE x SQRT of the sample size

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10
Q

What are trial and error heuristics?

A

Successively trying various different responses, seemingly at random, until one is successful

Maze learning, with its eventual elimination of blind-alley entrances, is an example of trial-and-error learning

Derived from Thorndike’s stimulus–response theory of instrumental learning (“trial-and-accidental success”)
- In animals, the reward reinforces the successful response, allowing the problem to be solved faster and faster

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11
Q

What are hill climbing heuristics?

A

Find some measure of the distance between the present- and goal-state

Take a step in the direction that most reduces that distance

Can be problematic – solution may involve moving away from the goal state before returning to it later

Prone to errors and suboptimal solutions (e.g., hill climbing robot)

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12
Q

What is mean ends analysis?

A

Somewhat like a “divide-and-conquer” approach

Identify obstacles between the current and goal state

Eliminate each obstacle in turn (each obstacle is a simpler sub-goal)

Once each sub-goal is achieved, you’ve reached your goal

E.g., GOAL=paint the house:
•Get paint and brush! (SUBGOAL 1)
•Go to hardware store (SUBGOAL 2)
•Buy paint and brush (SUBGOAL 3)
•Return home (SUBGOAL 4)
•Paint the house (GOAL)

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13
Q

What did Schacter do?

A

The Tower of Hanoi is a well-defined problem:
- Fully specified initial conditions
- Explicit goal state
- Clearly defined operators for transforming conditions
- Small solution space

Ill-defined problems
- No clear goals, or solution paths
- Unpredictable solutions
- Big solution space

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14
Q

Whats the Gestalt approach?

A

We perceive scenes and objects as familiar organised patterns or wholes (Gestalt grouping)

The key to problem solving is to deconstruct familiar “Gestalt” perceptions into their component parts

The problem can then be restructured in novel and more helpful ways

Revealing new (less obvious) relationships between items leads to insight

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15
Q

Whats the Gestalt Approach: The Einstellung Effect?

A

Mental set (persistence of set, negative set, entrenchment)

Old strategies continue to be used, when obviously ineffective

Incorrect problem representations

Relates to functional fixedness
- Tendency to use objects in conventional ways

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16
Q

Whats representational change theory?

A

Relax constraints on the problem to overcome mental set (Knoblich et al., 2001)

Have you decomposed all the problem features?

Try incubation: problems solved more easily if time set aside

Ormerod et al. (2009) meta-analysis (117 studies)
•Small but significant effect of incubation
•Larger effects for creative problems with multiple possible solutions
•Larger effects when more time had been spent on the task

Sleep on it (Beijamini et al., 2021)

17
Q

Whats the algorithmic approach?

A

A systematic sequence of steps that always provides the correct answer to a particular problem

E.g. finding your way out of a maze could be done simply be walking in the direction of the goal/target point

Generally, although it would guarantee a solution, it would be time-consuming

18
Q

What are brute force algorithms?

A

Go through all possible states until a solution is found

Guaranteed to work (eventually)

Impractical with large problem spaces

Problem: Unscramble the 10 letters to make a word
Almost a million alternative combinations!

19
Q

Whats analogical problem solving?

A

Analogies: relationship between two similar situations, problems, concepts

Difficulty lies in recognising structural commonalities between problems

Many problems are superficially dissimilar, yet strikingly similar at their core