I'm not sure you misunderstood as much as my poor explanation. Although rules of many games specify what winning is, in some cases strategy solutions don't necessarily have a clear definition of winning. Sometimes winning isn't defined as well as treating it as an optimization problem. There are rules of the game, and goals of the game.
As a simple example, take tic-tac-toe. There are rules (you can only put your marker, a X or O in a blank space) which specify what you can do. There are goals that evaluate your play, such as you win with three in a row in various directions, a draw where no one has three in a row, and a loss if your opponent gets three in a row.
There is no other real knowledge of how to play. An expert player will never lose, they will either win or draw based on known strategies that are unbeatable. The basic rules don't define how to do that.
What the learning system does is create strategies. A basic strategy might be, randomly put your X or O in an empty square. You could occassionally win against novice opponents that way. But it would not be an optimal strategy and would regularly lose. Evolve that strategy a bit and you find the system putting its X or O in a proximity which increases its ability to put three in a row. Evolve it a bit more and it can recognize that its opponent is trying to put three in a row and will block it. Evolve it a bit more, and it will block its opponent putting three in a row at the same time putting that block in an advantageous placement to benefit itself to win.
Nothing in the rules specifies this, but is the result of experience or math or research or intuition. The rule is just "The placement rules say you can do 'this'. The measurement of winning is defined as 'that'." The system "learns" from it's mistakes and successes.
Optimization problems are a little different, certainly multiple objective problems. In a more complex "game", you might be trying to optimize solutions for (really we're just talking about a problem domain and a solution space) the stock market, military strategy, chess, TTT, whatever.
The rules of military strategy for an objective can be unique. The rules of the game may be, minimize civilian casualties, you can only use certain type of weapons systems based on political situations, total cost must be under such-and-such, distances must be capable of being reached by units involved, certain enemy units must be captured rather than killed, etc.
Nothing in that tells you HOW to win, it just says, "Here are the rules you must follow, find the best way to do so that comes with the best chance of winning, costs the least, limited friendly-fire situations, etc."
So I guess that's what I mean when I say we don't tell it how to win. We measure winning as what our definition is and how close the strategy solution came to that goal. If it was poker, we would say, "here's the rules of texas hold 'em". The only measurement of winning would be amout of money won. We wouldn't tell it what the hand values were, what were considered good hole cards, or anything else. It would evolve the concept of when to win, bet, bluff, fold, how much to bet at a time, recognizing if it was being bluffed, when do do so based on how many players are in the hand, even what the values of the hands are, etc. At the end a few hundred games, we'd tell it, "Hey you were the best poker playing strategy or you were the worst strategy". That's it. The system evolves 'good' play on its own.
That's what I mean by not telling it how to win. We tell it how it measured against other strategies. It doesn't know what's going on.