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Time and Space Tradeoffs in search-artificial intelligence:
In practice, you need to stop your agent at some stage if it has not searched a solution by then. However, if we can choose the fastest search method, then this will explore more of the search space and increase the likelihood of finding a solution. However, there is a problem with this; It can be that the fastest method is the one which utilize most memory. To perform a search, an agent needs at least to know where it is in a search space, but lots of other things may also be recorded. For instance, a search strategy can involve going over previous ground, and it would save time if the agent knew it had already tried a particular path. Even though RAM capacities in computers are going steadily up, for some of the searches that Artificial Intelligence agents are employed to undertake, they frequently run out of memory. Thus, as in computer science in general, Artificial Intelligence practitioners often have to devise smart ways to trade memory and time in order to gain an effective balance.
-(9/14)log2(9/14)-(5/9)log2(5/9) calculate with solution.
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Specifying Search Problems In our agent expressions, a problem to be solved is a specific task where the agent starts with the atmosphere in a given state and acts upon the env
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