课程: AI Algorithms for Game Design with Python
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Depth-limited search
- [Instructor] So let's stop for a moment and ask ourselves, what's stopping us from doing better? Well, complexity. Minimax inherently runs on the depth-first search tree traversal algorithm. So it's really impossible to do the whole thing significantly faster. But wait, the fact that we cannot find a perfect solution to this problem in a short time doesn't mean that we cannot find a reasonable solution in a short time. This has been the key enabler to useful AI we are using today, like traffic apps or self-driving cars. A solution produced in a short amount of time doesn't have to be bad. So with this in mind, we could make some compromises. For example, we could prune further by identifying and skipping states that we've already seen. We could even push this to identifying rotations and reflections of already-seen states. We could also reduce b, the branching factor, by selecting the, say, three most promising moves while leaving unproductive or self-harming moves unchecked. And we…
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Depth-limited search3 分钟 50 秒
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Writing good evaluation functions6 分钟 55 秒
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Is alpha-beta pruning still relevant?2 分钟 32 秒
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Challenge: A depth-limited cat4 分钟 10 秒
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Solution: A depth-limited cat3 分钟 35 秒
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Challenge: Write your own evaluation function1 分钟 8 秒
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Solution: Write your own evaluation function3 分钟 7 秒
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