From the course: AI Algorithms for Game Design with Python
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The iterative deepening technique - Python Tutorial
From the course: AI Algorithms for Game Design with Python
The iterative deepening technique
- [Instructor] In most games, you have a time limit to analyze the game and think about your next move. Since we have to produce a move before the deadline, we could use depth-limited search, but two unwanted scenarios could come up. We could respond too late, in which case there may be a penalty, we might miss a turn or lose altogether. We could also respond too early, so early that maybe a deeper tree would've been possible, and thus a wiser move could've been made. The problem is that we have no guarantees as to how long the tree will take to compute, not even with a known limited depth. This is due to a variety of reasons. Some states might have more possible moves than others, we might prune off some branches, some terminal states might show up earlier than others, and the list goes on. So the question at hand is, how can we make the best use of our time? Here's a crazy idea called iterative deepening. Let's say we have two minutes to produce a move. So here's the plan, produce a…
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The iterative deepening technique2m 56s
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Is iterative deepening a waste of time?7m 41s
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Challenge: An iteratively deepening cat38s
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Solution: An iteratively deepening cat5m 27s
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Is iterative deepening really that good?2m 37s
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Is alpha-beta pruning really that good?4m 35s
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