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Statistical AI, arising from machine learning, tends to be more concerned with "inductive" thought: given a set of patterns, make the trend. Classical AI, on the other hand, is more concerned with "deductive" thought: given a set of constraints, assume a conclusion
A system can't be truly intelligent without displaying properties of both inductive and deductive thought. This lends many to believe that in the end, there will be some part of synthesis of statistical and classical AI.
Levels Of Parallel Processing Depending upon the difficulty under consideration, parallelism in the answer of the problem may be achieved at dissimilar levels and in different
Why a computer expect to receive responses when it broadcast an ARP request? Response will be acquired only from the machine for that request is being sent not for the other ma
What is data structure? A data structure is a way of organizing data that considers not only the items kept, but also their relationship to each other. Advance knowledge abo
Design Issues Of Interconnection Network The following are the problems, which should be considered while preparing an interconnection network. 1) Dimension and size of n
Question: (a) Primary and secondary memory differs in their way they access data: (i) Mention the four generic access methods usually present in a computer system. (ii) E
Explain about Behavioral Notations These notations contain dynamic elements of the model. Their elements comprise interaction and the state machine. It also comprise classe
Various Interconnection Networks Fully connected: This is the most controlling interconnection topology.In this each node is directly linked to all other nodes. The shortcomi
If two base classes have no overlapping methods or data they are said to be independent of, or orthogonal to each other. Orthogonal in the sense means that two classes function in
Load testing is to test that if the application works well with the loads that result from large number of concurrent users, transactions and to verify whether it can handle peak u
Examples of artificial neural networks: Now here as an example consider a ANN that has been trained to learn the following rule categorising the brightness of 2x2 black and wh
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