Choose Training Experience

• how well training experience represents the distribution of examples over which the final system performance P must be measured
• P is percent of games in the world tournament, obvious danger when E consists of only games played against itself (probably can't get world champion to teach computer!)
• most current theories of machine learning assume that the distribution of training examples is identical to the distribution of test examples
• It is IMPORTANT to keep in mind that this assumption must often be violated in practise.
• E: play games against itself (advantage of getting a lot of data this way)