CS 484 - Artificial Intelligence
Fall 2005
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Homework 6
1) Give three computer applications for which machine learning approaches seem appropriate and three for which they seem inappropriate. Pick applications that were not mentioned in the lecture, and include a one-sentence justification ffor each.
2) Consider alternative strategies for the Experiment Generator module on the "Final Design" slide at the end of Lecture 14. In particular, consider strategies in which the Experiment Generator suggests new board positions by
- Generating random legal board positions
- Generating a position by picking a board state from the previous game, then applying one of the moves that was not executed
- A strategy of your own design
Discuss tradeoffs among these strategies. Which do you feel would work best if the number of training examples was held constant, given the performance measure of winning the most games at the world championship?
3) Explain why the size of the hypothesis space in the EnjoySport learning task is 973 (from Lecture 16). How would the number of possible instances and possible hypotheses increase with the addition of the attribute WaterCurrent, which can take on the values Light, Moderate, or Strong? More generarally, how does the number of possible instances and hypothesis grow with the addition of new attribute A that takes on kpossible values?