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4

In a game-theoretical sense, both of the moves you describe are equally good in the scenarios you describe, so the algorithm is "correct" in that it doesn't matter which move it picks -- you do not explicitly encode a preference for faster wins (or faster gains of $+100$) over slower scores. Introducing a discount factor to explicitly encode such a ...

3

This is because you are not using a discount factor in your search. A discount factor $\gamma$ is a number between 0 and 1. The discount factor describes the preference of an agent for current rewards over future rewards. When $\gamma$ is close to 0, rewards in the distant future are viewed as insignificant. When $\gamma$ is 1, discounted rewards are ...

2

By definition, minmax chooses the move that results in the best possible outcome if the adversary plays optimally, but within the bounds of what the evaluation function takes into account. More precisely, minmax results in the best outcome that can be guaranteed no matter how the adversary plays, as long as the adversary's behavior is no worse than what the ...

1

In the rules of chess, one player can demand a draw when the same position is entered three times. If your opponent can demand a draw, the value of the position is 0 in the best case. So if you look forward far enough, you see that a move leading to repetition may not be that good. (In this case, you would choose the second best move if it has a value > 0, ...

1

You write a function that looks at a position and gives it a value. The value should be higher for good positions and lower for bad positions. Strategy 1: You try all your possible moves, evaluate the position after each move, and pick the move that produces the highest value. Strategy 2: You try all your possible moves, then assume that the opponent ...

1

In minimax you fully explore the game tree. So the answer to "which piece" is all of them. All possible moves for all movable pieces. And then it selects the minimum or maximum (depending on the depth) out of those options. Obviously this isn't feasible which is why we never apply raw minimax to chess. It is always with other optimizations such as alpha-...

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