Systems with embedded rules.

Consider the direct and inverse chain analysis on the example of an imaginary set of rules on how to spend an evening. The rules are as usual, antecedent located on the left, as a consequence - the right, due to all regulations are met, a review is conducted in parallel.
1. A good movie on TV + Early morning meetings no later films ®
2. Early morning meetings do not + We need to work late ® Jobs
3. We need to work + required documents ® Work in the office
4. Later films ® Do not sleep late
5. Work late ® Do not sleep late
6. Work late ® Return to the office
7. Work in the office ® Return to the office

For example, Rule 1 states that if the TV is a good movie and I have tomorrow early morning meetings do not, then I follow the regime of "later a movie".
Consider the first example of direct chain analysis. Assume that the system has received initial information that the sooner tomorrow utorm I do not have meetings. Activated rules 1 and 2. Assume further that the system received a message that I need to work on. Active Rule 3 and Rule 2 is called and vypolnyaetya, whence the conclusion that I was in a "work late", with the result that triggered and implemented rules 5 and 6. As a result, the system is that I should go back to the office and do not sleep late.

Now consider the same problem with the use of a chain of analysis. Assume that the system has received background information that I do not have a meeting tomorrow morning, but I need more work, then it (the system) was asked whether I go back to the office. This request activates the rules 6 and 7. In turn, there is the question "Working late" or "Work in the office? This enabled the rules 2 and 3, and the question is "Early in the morning meetings do not," "We need to work" or "required documents"? The first two antecedent are satisfied, so rule 2 will be called and executed, which would entail the satisfaction of antecedent "Working late, call and execution of rule 6, in which the system will come to the conclusion that I should go back to the office.

Please note that the direct parsing generated more consequences, and if the reverse - requests. Since in both cases used the same data, in the course of the analysis performed by the same rules, but activated different.