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Artificial Intelligence research:
Artificial Intelligence research may be describe in terms of how the following question has been answered:
"How are we going to get a computer to perform intelligent tasks?" One way to answer the question is to say that:
This has going to use of logic - drawing on philosophy and mathematics - in a big deal of AI research. This means that we may be very specific about the algorithms we implement, write our programs in very clear and neat ways using logic programming languages, and even prove the things regarding the programs we produce.
However, when it's theoretically possible to do sure intelligent things (such as prove some simple mathematics theorems) with programs depend on logic alone, such methods are held back by the very big search spaces involved. People started to think about heuristics - rules of thumb - which they could use to enable their programs to get task done in a sensible time. They answered any question like this: · We're not sure that humans reason with perfect logic all the time, but we are certainly intelligent. So, let's use introspection and tell our AI programs how to think like us.
In answering this question, AI researchers started building expert systems, which encapsulated factual, procedural and heuristic knowledge about particular domains.
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• Multilevel feedback queue-scheduling algorithm enables a process to move among queues. It uses a number of ready queues and acquaintances a dissimilar priority with every queue.
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