chapter 9 Flashcards

1
Q

4 perspectives on goals

A
  1. design perspective

> find a very good solution at least once

  1. production perspective

> find a good solution at almost every run

  1. publication perspective

> must meet scientific standards

  1. application perspective

> good enough is good enough

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2
Q

2 basic rules of experimentation

A
  1. EAs are stochastic

> never draw conclusions based on a single run

  1. EA experimentation is about comparison

> use same amount of resources

> try different comp. limits

> use same performance measure

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3
Q

3 performance measures

AES

SR

MBF

A

AES = average number of evaluations to solution

SR = success rate, % of runs finding solutions

MBF = mean best fitness

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4
Q

what is the problem with hidden labour

A

hidden labour: heuristic mutation operators might result in bias when comparing numbers of evaluations nbetween algorithms

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5
Q

what are 3 general performance measures?

A
  1. robustness
  2. speed
  3. solution quality
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