WEEK 1

Question 1

What is a Generic Evolutionary Algorithm?

Answer 1

You have a solution s and a function f(s) which measures how good s is.
Generate P random solutions, evaluate fitness of each.
Go through Selection, Variation, & Population Update.

Question 2

How do we select EA solutions?

Answer 2

Select the best - bad results, quickly (local minima)
Randomly - great results, way too slow

Question 3

Exhaustive search (enumeration)

Answer 3

Generate every possible solution, compute its fitness, and hence discover which is best

Question 4

What are the kinds of problem?

Answer 4

Easy (in P ‘tractable’)
Hard (not in P ‘intractable’)

Question 5

What are approximate algorithms?

Answer 5

Deliver solutions in reasonable time
Try to find ‘near optimal’ solutions, often optimal
Cannot guarantee its the best solution. Evolutionary are the most successful and useful approximate algorithms around.