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Case Based Reasoning: A Framework

Rafi Ahmad Khan, Sharfa Hassan

Abstract


Case based reasoning is an extended research field in Artificial Intelligence. It is an Artificial Intelligence technique for problem solving by using past experiences. The concept emerged in US and now it has spread to other continents with Europe having the most active research in Case based reasoning (CBR). Most of the Artificial Intelligence techniques are confined to a general knowledge base of the problem domain and then making generalized inferences to solve a problem. But CBR as an Artificial Intelligence (AI) technique brings the element of actual human behavior to the domain of AI. CBR relies on experiences with the help of which it reasons and solves the problem situation. This approach to AI has really captured the essence of human intelligence which improves with their age. CBR not only keeps the database of past experiences, but with more use of its experiences its reasoning improves. It updates its memory and learns from what it does that makes it different from other AI approaches.  Therefore, learning is an important aspect in case based reasoning. In this paper first the working of a typical CBR system is presented followed by some application areas where it will be seen to what extent this concept has been used in actual practice.


Keywords


Artificial Intelligence (AI), Case Based Reasoning (CBR), Problem Solving, Learning, Experience.

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References


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