Case Based Reasoning (CBR) vs Rule Based Reasoning (RBR)

Sunday, December 23, 2007 | Labels: , | 1 comments |

Rule Based Reaoning (RBR) requires us to elicit an explicit model of the domain. As we all know and have experienced, knowledge acquisition has a set of associated problems. In contrast, Case Based Reasoning (CBR) does not require an explicit model. Cases that identify the significant features are gathered and added to the case base during development and after deployment. This is easier than creating an explicit model, as it is possible to develop case bases without passing through the knowledge-acquisition bottleneck.

Domain experts would have accumulated knowledge over the years through experience. It would be a blunder mistake if we do not use them to our advantage. But the difficulty lies in getting the experts to list down the decision rules which they use. It is a Herculean task to comprehensively recall all the tacit rules which they have come to adopt. However, they usually have little difficulty in recalling concrete cases, which they have encountered in practice. Thus, their mental set appears to be oriented towards a Case Based Reasoning approach.

Developing a CBR system is much faster and easier than constructing a rule-based equivalent. Case bases do not have to be complete when they are deployed for use, as even non-computer experts can add cases to the existing structure.

Maintenance with a Rule Based System may be a nightmare. If the rules are not written clearly, it would lead to many sleepless nights of debugging. Maintenance with Case Based Systems are much easier and straightforward.

When rules are added or deleted from a rule-based system, the system has to be checked for conflicting rules and redundant rules. An addition or deletion of a case from the case base does not any further checking or debugging. But it have to be noted that while it does not affect the system’s functioning, it may have an impact on the outcome of the system.

Problem Approach in CBR

Saturday, December 22, 2007 | Labels: | 0 comments |

In an earlier post, we saw what exactly is Case-Based Reasoning (CBR). Here, we are going to see how CBR approaches a problem.

CBR revolves around case base, a database of past cases, that typically contains cases with problem description, possible causes and solutions. Don't confuse yourself with case base and database. They are similar, but not the same. Database works on crisp data and exact solution match, whereas CBR is based on fuzzy match. CBR has the ability to learn and improve, whereas databases do not.

In CBR, a new problem is solved by finding a similar past case, and reusing it in the new problem situation. Note the word similar. CBR would give a solution even if you don't get an exact match. If you accept the solution, then it goes into the case base as another case. If the solution is not accepted, it gives CBR a learning step.

The following four steps summarize how a problem is solved in CBR:
  1. Search for the most similar case (or cases) comparing the present case to the past cases in the case base
  2. Retrieve and Use the case to solve the current problem
  3. Revise and adapt the propose solution if necessary
  4. Save the solution as part of a new case

Do ants leave there saliva?

Friday, December 21, 2007 | Labels: | 2 comments |

This post is mainly to try out a SEO (Search Engine Optimization) technique from Vic at Blogger Unleashed. Vic's new blog was indexed and ranked number one for the term "Do ants scratch there ass?". The same technique was used by Grizz in his post to be ranked number one for the term "Do ants scatch there ass?"

Now, it is my turn to try out the term "Do ants leave there saliva?" You could have noticed the spelling mistakes, but just ignore them. They were intentionally made. I am doing this understanding only half the technique. But, who cares? If I can get the indexing by Google, then it will be a lot better for this blog.

Just ignore this post if you are looking for any tips on Artificial Intelligence or Knowledge Engineering. I will be coming out with posts on the topics related to Artificial Intelligence/ Knowledge Engineering soon.

What is Case Based Reasoning?

Thursday, December 20, 2007 | Labels: | 0 comments |

Case-Based Reasoning (CBR) is a problem solving model that is fundamentally different from other major Artificial Intelligence (AI) techniques.

CBR does not rely solely on the general knowledge of a problem domain. CBR is able to make use of the specific knowledge of previously experienced concrete problem situations. These previous situations are referred to as cases in CBR.

CBR uses an incremental approach to sustained learning, since a new experience is retained each time a problem has been solved, making it available for future problems.

In the next post, we will see how to solve problems using CBR.

A blog on Artificial Intelligence

Wednesday, December 19, 2007 | Labels: | 0 comments |

This is my new blog. Here, I am going to share with you my knowledge on topics like Artificial Intelligence, Knowledge Engineering, Neural Networks, Case Based Reasoning, Intelligent Agents, Rule Based Reasoning, Fuzzy Systems, Genetic Algorithms and other related topics.

I am still in the process of setting up this blog. When the tweaking of the layout is complete, I will start posting the discussions. Until then, good bye.