Artificial intelligence seminar topic covers detailed information on requirements of an artificial intelligence system , areas of artificial intelligence.
Students can refer to Seminar presentation on related topic with free PPT download.
Interesting Features in Artificial Intelligence:
The speed of computation and neural networks are some of the features that make a system more intelligent. It also includes filtering and displaying of responses that are meaningful and also provides a solution to a particular question. Plus, the algorithms divide the task into several subtasks called recursion.
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Similar like that of humans brain, computers also sometime face the problems of understanding a particular situation and adapting to a new one. The behavior of the machine improved only due to the artificial intelligence. The improved behavior helps in tackling the complex jobs that are based on the deliberate reasoning of high level, abstract thoughts and recognition of patterns. The artificial intelligence can help in understanding the process by recreating it. It helps to enhance it beyond the capabilities of the present situations.
Ambiguity makes it difficult to understand the meaning that is intended for certain sentences and phrases. It also makes difficult to understand the inferences. Symbolic logic is an unambiguous knowledge representation that is developed originally in order to formalize the attempt for reasoning of mathematics.
The limitation of semantic networks is the structure that is added which also makes it necessary for distinguishing. The object properties and relationships of the statement are the two distinguished features of the frames. A frame comes with structures in addition and it is simply a node that facilitates the relationships between the object properties and the objects itself. It is known as a representation of “slot-and-filler”.
Reasoning for monotonic:
With time the facts also change
A gather of facts never reduces
The system of monotonic reasoning is very effective for solving problems in various situations.
Principles of NMRs
Y is concluded if the x is unknown.
Again y is concluded if x is not proven
Default reasoning is essential in the presence of incomplete details.