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Foundation of Cognition > Lecture_08_Reasoning & Problem Solving > Flashcards

Lecture_08_Reasoning & Problem Solving Flashcards

1
Q

Formal Rules of Logic

A
  1. Deductive reasoning
  2. Inductive reasoning
  3. Conditional reasoning
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1
Q

Reasoning

A

Drawing conclusions by putting statements (premises) together using logic
1) to make sense of our present experiences and ideas, and to plan for the future
2) to establish and verify facts

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2
Q

Premise

A

Statement of fact that is assumed to be true

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3
Q

Deductive Reasoning

A
  • Top-down reasoning”
  • If the premises are true, the conclusion must also be true.
  • Premise 1: All cognitive processes involve brain activities.
  • Premise 2: Memory is a cognitive process.
  • Conclusion: Memory involves brain activities.
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4
Q

The Problem of Deductive Reasoning

A
  • What’s important is the form of the argument
  • The truth of the premise in the real world & your prior knowledge are irrelevant!
  • Premise 1: All birds have wings.
  • Premise 2: Unicorns are birds. (?)
  • Conclusion: Unicorns have wings.
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5
Q

Inductive Reasoning

A

Bottom-up reasoning
- If the premises are true, the conclusion is also LIKELY to be true.
- Premise 1: Restaurant A has many delicious dishes.
- Premise 2: You order an omelet.
- Conclusion: The omelet is delicious.

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6
Q

The Problem of Inductive Reasoning

A

The conclusion is likely, but it’s NOT guaranteed to be true.
- Based on probability.
- 80% of brain surgeons are men.
- Lee is a brain surgeon.
- Lee is a man.

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7
Q

Conditional Reasoning

A

If P-then Q
- Deductive reasoning that involves conditional statements
- Premise 1: If P, then Q
- Premise 2: A statement about whether P or Q is true or not true
- Conclusion: A statement about whether P or Q is true or not true

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8
Q

2 Valid Forms of Conditional Reasoning

A
  1. Affirming the antecedent (modus ponens)
  2. Denying the consequence (modus tollens)
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9
Q

Premise 1: If P, then Q
Premise 2: P
Conclusion: Q

A
  • Valid
  • Affirming the antecedent
  • Modus ponens
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10
Q

Premise 1: If P, then Q
Premise 2: Q
Conclusion: P

A
  • Invalid
  • Affirming the consequence
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11
Q

Premise 1: If P, then Q
Premise 2: ~P
Conclusion: ~Q

A
  • Invalid
  • Denying the antecedent
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12
Q

Premise 1: If P, then Q
Premise 2: ~Q
Conclusion: ~P

A
  • Valid
  • Denying the consequence
  • Modus tollens
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13
Q

Wason’s Card Selection Task

A
  • 4 cards
  • Each card has two sides: a letter and a digit.
  • Rule: If a vowel is on one side, there is an even number on the other side
  • Try to confirm this rule by turning over the fewest number of cards
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14
Q

Why do participants make mistake in Wason’s Card Selection task?

A

People make mistakes by seeking verification rather than falsification

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15
Q

Logical Fallacies

A
  1. Begging the question
  2. After this, therefore because of this
  3. Ad hominem
  4. Slippery slope
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16
Q

Begging the question

A

Assuming the truth of the conclusion, rather than supporting it
- E.g. Humans help each other because of their kindness

17
Q

After this, therefore because of this

A

Correlation isn’t causation
- X occurred, then Y occurred
- Therefore, X caused Y
- E.g. Nearly all heroin addicts used marijuana before they tried heroin. Clearly, marijuana use leads to heroin addiction

18
Q

Ad Hominem

A

Criticizing an individual who makes an argument
- E.g. Freud used cocaine. Therefore, we should not bother reading his books

19
Q

Slippery Slope

A

Because after stating A and B condition, there aren’t condition of C, D, E, or more
- Series of incremental inferences to arrive at undesirable conclusion
- E.g. If we allow gay marriage, the next thing we know, people will want to marry their dogs, or their cats, or what about their pigs?

20
Q

Mental Models of Reasoning

A

People create, combine, and evaluate specific possibilities
- Premises are stored in a concrete, meaning-based format, rather than in an abstract logical way
- Premise 1: All birds are animals
- Premise 2: Some animals are large
- Conclusion: Some birds are large
- Invalid

21
Q

Why do people make reasoning errors according to mental models?

A

People did not consider enough possibilities (mental) models
- Limited by working memory capacity

22
Q

Bayesian (Probability) Models of Reasoning

A
  • People make judgments based on probabilities, rather than engaging in pure deductive reasoning
  • When people answer incorrectly on reasoning tasks, it’s because they treat them as probability tasks
23
Q

An Example of Inference Based on Probability: Dog and Fur

A
  • Premise 1: There’s a high probability that a dog has fur
  • Premise 2: Some don’t, but it’s a pretty good guess
  • Conclusion: Therefore, Rover has fur
  • When you hear “Rover is a dog”, you assume that Rover has fur.
24
Q

Dual-Process Models of Reasoning

A
  1. System 1 – Fast cognition, associative process, outside consciousness
    - Pragmatic reasoning
    - Prone to errors
  2. System 2 – Slow cognition, rule based and logical
    - Allows us to try to apply rules of logic!
    - But, limited by working memory
25
Q

Why do people make errors in problem solving tasks according to the dual-process model?

A

They’re relying on System 1 instead of System 2”
- Because it’s easier, faster, and requires less cognitive resources

26
Q

Problem

A

Any situation in which a person has a goal that is not yet achieved

27
Q

Well-Defined Problems

A

Clearly defined goal state and constraints

28
Q

Ill-Defined Problems

A
  • Unclear goal state and constraints
  • Difficult to create mental representations and identify a solution
29
Q

Information Processing Approach

A

Problem-solving = “searching” through a space consisting of all possible states of the problem

30
Q

Information Processing of Problem-solving

A
  1. Create a PROBLEM SPACE to represent the problem. Include the initial state, goal state, instructions, constraints, and relevant info from long-term memory.
  2. Select OPERATORS – actions that will transform the initial state.
  3. Implement the operators – results in a new current state within the problem space.
  4. Evaluate the current state – if it corresponds to the goal, a solution is reached
31
Q

General Problem Solver (GPS)

A

Computer program based on information processing framework
- Remarkable similarity between GPS algorithm & what human participants report out loud while solving a problem

32
Q

How to select operators to solve a problem?

A

Algorithmic Vs. Heuristic Strategies

33
Q

Algorithms

A

Methods that are guaranteed to lead to the solution, if followed correctly
- E.g., mathematical rules ( 998 / 21 = ? )
- But sometimes can’t use them, due to memory constraints or other processing limitations

34
Q

Heuristics

A

Methods or strategies that often lead to the solution
- But, not guaranteed to always succeed!

35
Q

Means-End Analysis

A
  1. Compare the CURRENT STATE with the GOAL STATE.
  2. If there are differences, solve the LARGEST DIFFERENCE.
  3. Select an OPERATOR that will solve the difference.
  4. Apply the operator. If it cannot be applied, set a new goal (i.e., a SUB-GOAL) to reach a state that will allow the application of the operator.
  5. Solve this sub-goal by REPEATING 1-4
36
Q

Analogy

A

PRIOR EXPERIENCES and BACKGROUND KNOWLEDGE can be helpful
- Classify and understand the problem
- Automatize some problem-solving steps
- Draw analogy from past experiences
1) Surface similarity
2) Structural similarity

37
Q

Insight

A

the solver feels like they suddenly arrive at the solution (“Aha!”)
- Usually requires looking at the problem in a different way from the usual way

38
Q

Incubation Effect

A

Insight can occur even when you’re not consciously thinking about the problem

39
Q

What blocks insight?

A
  • Self-imposed constraints
  • Functional fixedness

Foundation of Cognition (15 decks)

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