JPH05282152A - Device and method for managing knowledge base - Google Patents

Abstract

PURPOSE:To reduce the redundancy of a rule in a knowledge base, to hold compatibility and to attain systematization by analyzing plural different condition values, detecting a redundant condition value between rules and changing the condition value. CONSTITUTION:A knowledge comparing part 104 extracts a rule from a knowledge base 100 and judges whether a condition part and a consequence part are mutually different or not by a condition part comparing part 106 and a consequence part comparing part 110. A condition value analyzing part 108 in the comparing part 106 compares and analyzes individual condition values and detects a redundant condition value. The pattern of the condition value, the redundant condition value and the information of the consequence part which are obtained from the comparing part 104 are transmitted to a knowledge polishing part 116, a new condition value pattern is formed by a condition value changing part 114 to form a new rule 120. The new rule is recorded in the base 100 and the preceding processing is repeated to manage the knowledge base storing rules having no redundancy.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a knowledge base management apparatus and method for performing knowledge processing including an expert system, and is particularly suitable for managing redundant rules in a knowledge base and detecting inconsistencies. Related knowledge base management apparatus and method.

[0002]

2. Description of the Related Art The use of a knowledge base used in an expert system has the following problems.

First, when knowledge is added to the knowledge base, the knowledge may become redundant.

Next, when the number of rules in the knowledge base is increased, it is difficult to maintain consistency between the rules. This is because the reasoning system will not work if multiple rules make contradictory conclusions. In particular, when debugging a knowledge base or adding a new rule to an existing knowledge base, it is necessary to eliminate inconsistencies between the knowledge and ensure consistency.

[0005] To solve the above problems, as a conventional technique, "knowledge refinement support system using cases" (Information Processing Society of Japan 41st (second half of 1990) National Convention Proceedings Vol. 2, 53)
~ Page 56).

In this technique, the rule group in the knowledge base is expressed in the following tree structure format.

Rule: (Value of Condition 1 ... Value of Condition M Conclusion) This expression means that the conclusion is satisfied if the conditions 1 to M are satisfied. Here, a combination of condition values for each rule is defined as a condition value pattern.

The matching process between the rules is as follows. First, the condition value pattern of the newly added rule is compared with the rule in the knowledge base. Next, the rule in the knowledge base having only one different condition value is detected. However, the condition values that are not included in the condition part of the newly added rule are not included in the comparison. Finally, modify the rule by modifying different condition values.

Regarding the change of the rule in the prior art,
This will be described with reference to FIGS. 11 to 14. FIG. 11 shows a case where neither the condition value pattern of the new rule nor the consequent part exists in the knowledge base. Here, consider an example in which the new rule is (a1 b2 c) and the existing rule in the knowledge base is [(a1 b1 b) (a2-b)]. In this case, since only a1 is equal, one branch is added and the knowledge base is updated as follows.

[(A1 b1 b) (a1 b2 c) (a2-b)] FIG. 12 shows that the condition value pattern of the new rule does not exist in the knowledge base, but the consequent part exists in the knowledge base. Is. Here, consider an example in which the new rule is (a1 b2 b) and the existing rule in the knowledge base is [(a1 b1 b) (a2-ro)]. In this case, the condition value for condition B is rewritten and the knowledge base is updated as follows.

[(A1 b1 or b2 b) (a2-b)] If there is meta-knowledge that the condition B only takes b1 and b2, the condition B can be omitted, and the condition is as follows.

[(A1-i) (a2-b)] FIG. 13 shows a case where the condition value pattern of the new rule has a common part in the knowledge base, but the consequent part does not exist in the knowledge base. .. Here, consider an example in which the new rule is (a2 b2 c) and the existing rule in the knowledge base is [(a1 b1 b) (a2-b)]. In this case, the condition B of the knowledge base is b
With the knowledge that there are only 1 and b2, the knowledge base can be updated as follows.

[(A1 b1 b) (a2 b1 b) (a2 b2 c)] FIG. 14 shows that the condition value pattern of the new rule exists in the knowledge base, but the consequent part does not exist in the knowledge base. Is. That is, when the new rules conflict with the existing knowledge base. Here, consider an example in which the new rule is (a2-c) and the existing rule in the knowledge base is [(a1 b1 b) (a2-b)]. In this case, an inquiry is made as to whether there is a new condition for distinguishing the new rule from the existing rule. If it can be distinguished by the condition N, the knowledge base can be updated as follows.

[(A1 b1-a) (a2-n1 b) (a2-n2 c)]

[0015]

In the conventional technique, when the rules are compared with each other, only the condition value patterns are simply compared. Therefore, the conventional technique can be applied only when the condition values are different by one kind. There is a problem.

Further, in the conventional technique, even if a plurality of condition values are different in some rules, the redundant condition values that can be found by comparing and analyzing the condition values cannot be removed. There's a problem.

Therefore, an object of the present invention is to change a plurality of condition values by comparing the condition value of the condition part between the rules and the consequent part, and remove the redundant condition in the knowledge base. An apparatus and a method thereof are provided.

Another object of the present invention is to provide an apparatus and method for detecting a contradiction between rules and maintaining the consistency of a knowledge base by comparing the condition value of a condition part between rules and the consequent part. Is.

[0019]

In order to achieve the above object, the present invention is, as an example, a knowledge base management apparatus having a knowledge base, and a condition value for analyzing a condition value constituting a condition part between rules. It has a condition comparison unit that includes an analysis unit and a knowledge comparison unit that includes a result comparison unit that compares the result units.As a result of comparing each condition unit and the result unit, multiple condition values can be combined, divided, or deleted. It has a knowledge value refinement unit that creates a new rule based on the result of changing the condition value, including the condition value changing unit, and stores the new rule in the knowledge base to create a new rule without redundancy. create.

[0020]

According to the present invention, by comparing the condition values of the rules and the consequent part and analyzing a plurality of different condition values, redundant condition values between the rules are detected, and the condition values are changed. , It is possible to reduce the redundancy of rules in the knowledge base, maintain consistency, and systematize.

[0021]

2 is a block diagram of a knowledge base management apparatus according to an embodiment of the present invention. An outline of the configuration and operation of the entire device will be described.

The device comprises a control device (CPU) 200, a main memory 206, a magnetic disk 208, a CRT 202 and a keyboard 204. The knowledge base 100 is stored in the magnetic disk device 208. Also, the knowledge comparison unit 1
04 and programs of the knowledge refining unit 116 are also stored in the magnetic disk device 208. The keyboard 204 is used for program instructions. The CRT 202 is used to display the result.

The programs of the knowledge comparison unit and the knowledge refinement unit and the contents of the knowledge base are loaded into the main memory 206 as needed. This operation is performed from the keyboard 204. The keyboard 204 also designates a command for calling the programs of the inference unit and the inference control unit into the main memory 206 and an execution start command. The inference process and results are displayed on the CRT 202.

The present invention will be specifically described below. First,
The outline of one embodiment will be described. FIG. 1 shows the entire program and data structure. The knowledge comparison unit 104 fetches a rule from the knowledge base 100, and the condition comparison unit 106 and the consequent unit comparison unit 110
It is determined whether the conditional part and the consequent part are different from each other. Furthermore, the condition value analysis unit 10 of the condition comparison unit 106
At 8, the individual condition values are compared and analyzed to detect redundant condition values. The condition value pattern, redundant condition value, and consequent part information obtained from the knowledge comparing unit 104 are transmitted to the knowledge refining unit 114, and the condition value changing unit 114 generates a new condition value pattern to generate a new rule. Create 120. By recording this new rule 120 in the knowledge base 100 and repeating the above processing, it is possible to manage a knowledge base having rules without redundancy.

Next, the processing of the knowledge comparing section and the knowledge refining section will be described with reference to FIGS. First, the rule to be compared is recorded (302), and it is checked whether the recorded condition value pattern of the rule matches the condition value pattern of another rule in the knowledge base (304). If there is a match of the condition value patterns, the consequent parts are compared between these rules (306). If the consequent parts also match, the rule to be compared is the same as the other rules in the knowledge base, so the knowledge base is not updated and the process ends (320). Also, as a result of comparing the consequent parts in 306,
If the resulting part of the compared rule is a subset of the resulting part of the rule in the knowledge base, then the compared rule is a narrow interpretation of the other rules in the knowledge base. Ends without updating (320).

In 306, if there is no matching consequent part, there is a rule having the same condition value pattern but different conclusions from each other. Therefore, the rule to be compared is the other rule in the knowledge base. Inconsistent with the rules. Therefore, the contradiction removal process (308) is performed. This process will be described with reference to FIG.

On the other hand, if the condition value patterns are different in 304, it is checked whether or not the condition part of the rule to be compared is a subset of the condition part of the rule in the knowledge base (310). .. If they are subsets, the resulting parts are compared between these rules (31
2). If the consequent parts also match, the rule to be compared is satisfied with less conditions than the other rules in the knowledge base, so the existing knowledge base is redundant. Therefore, processing for removing redundancy is performed (314).

In 312, if the consequent parts do not match, the rule to be compared is inconsistent with other rules in the knowledge base, so the process for removing the inconsistency is performed (308).

Further, in 310, it is checked whether or not the result part of the rule to be compared is the result part of the condition part of the rule in the knowledge base (316). If the consequent parts match, the rule to be compared may be redundant with other rules in the knowledge base, and therefore the process of removing redundancy (316) is performed.

If the consequents do not match in 316, the rule to be compared is different from the other rules in the knowledge base, so that rule is added to the knowledge base as a new rule (318).

The processing of redundancy elimination 1 in 314 of FIG. 3 will be described with reference to FIG. In this case, the rule to be compared is satisfied with less conditions than the other rules in the knowledge base, so the existing knowledge base is redundant.
Therefore, the rule to be compared is registered in the knowledge base (402), and the existing rule is deleted from the knowledge base (404).

The process of redundancy elimination 2 in 316 of FIG. 3 will be described with reference to FIG. First, if there is only one kind of different condition value among different condition value patterns (50
2) By taking the union of those condition values (50
4) Modify the condition values and combine them into one rule (50
6) Register with the knowledge base (520). Then, the existing rule is deleted from the knowledge base (522).

In 502, when there is not one kind of different condition value, it is checked whether there is a condition value having an overlapping relation between the rules (508). If there are overlapping values, those condition values are divided into overlapping parts and non-overlapping parts (510). For a condition value pattern having an overlapping portion (512), it is checked whether or not there is a condition value having a reciprocal relation between these rules (514).
If there is a condition value having a discharge relation, the condition value having a discharge relation may be any value in the range of the overlapping condition values described above, so that the condition value having a discharge relation is removed from the condition value pattern. By doing so (516), the rules are modified (518).

At 512, even if the condition value pattern does not have an overlapping portion, the condition value is changed to modify the rule (518). These processes are repeated among all the rules in the knowledge base until there is no condition having an overlapping relation in the condition value at 508 or there is no condition having a contradictory condition value at 514. A rule without redundancy is created and registered in the knowledge base (520). Then, the existing rule is deleted from the knowledge base (522). By the processing described with reference to FIG. 5, the redundancy of the knowledge base can be reduced.

The process of removing the contradiction in 308 of FIG. 3 will be described with reference to FIG. First, the user is informed of a contradiction (602) and asked if there is a new condition value to be added to resolve the contradiction (604). If there is a new condition value to be added, the condition value is added to the condition value pattern to modify the rule (606), and the modified rule is registered in the knowledge base (608). Then, the existing rule is deleted from the knowledge base (610). If there is no new condition value to be added in 604, it is informed that the rule to be compared is inconsistent with other rules in the knowledge base (612). The processing described with reference to FIG. 6 makes it possible to maintain the consistency of the knowledge base.

In the above description, the redundancies are removed for the rules existing in the knowledge base in advance, but this process adds a new rule 704 to the existing knowledge base 700 as shown in FIG. It can also be applied when doing. Others are the same as in FIG.

Further, since the present invention compares the rules with each other, the knowledge base matching including the rule contradiction detection 610 in the knowledge base is detected by using the process corresponding to the contradiction described in FIG. It can be applied as a treatment that preserves sex. Furthermore, the present invention has application in debugging knowledge bases under construction.

Next, an example in which the present invention is applied to the deletion of simple rule redundancy will be described with reference to FIG. In FIG. 8, consider the case where the consequent part is the same and the condition part is given two rules 1 and 2. The condition value is different between the condition A and the condition B. Here, it is assumed that the condition B is only b1 and b2. As for condition A, a2 is duplicated, so rule 1 is rule 1-1, rule 1-2 is rule 2-
It is divided into 1, 2-2. Then, the rule 1-2 and the rule 2-1 have the condition A in common and the condition B has an anti-relationship relationship, so the condition B is deleted and a new rule 3 is created. Therefore, in rule 3, only a2 needs to be satisfied.

Next, an example in which the present invention is applied to the management of the knowledge obtained by the behavior inference of the Schmitt trigger, is a circuit diagram of the Schmitt trigger circuit, and FIG. 10 is an input / output characteristic.
Will be explained. Like reference numerals refer to like elements in the two figures. This circuit has a power supply voltage (Vcc) of 8
By adding 04 and increasing / decreasing the input voltage (Vi) 800, the output voltage (Vo) 802 has an input / output characteristic with hysteresis as shown in FIG. Here, V1 (901) is the value of the input voltage at which the value of the output voltage changes from the power supply voltage 804 to the low value (V3) 904. V2
(902) is the value of the input voltage that undergoes the opposite change. The following knowledge can be obtained by performing a simulation of increasing the input voltage 800 from 0 until the output voltage 802 is saturated and a simulation of decreasing the input voltage 800 from the state where the output voltage 802 is saturated.

(1) When the input voltage (Vi) is increased (a) When dVi / dt> 0, 0 ≦ Vi <V2 V
o = V3 (b) When dVi / dt> 0 and V2 ≦ Vi, Vo = V
cc (2) When input voltage (Vi) decreases (c) When dVi / dt <0, V1 <Vi Vo =
Vcc (d) dVi / dt <0, Vo when 0 ≦ Vi ≦ V1
= V3 Among the above four rules, comparing (a) and (d), the condition part is different (304), but the consequent part is Vo = V3
And the same (312). About these two rules V
Regarding i, the range of 0 ≦ Vi <V2 overlaps (508). The condition value for Vi is divided (51
0) and dVi / dt can take both positive and negative in the overlapping range, the condition of dVi / dt is anti-reciprocal relation (514). Therefore, the value of dVi / dt may be any value in this range. Therefore, by removing this condition as redundant (516),
The following two rules can be created instead of the rules of (a) and (d).

(E) When 0 ≦ Vi <V1, Vo = V3 (f) When dVi / dt <0 and V1 ≦ Vi ≦ V2, V = V3
o = V3 Similarly, the following two rules can be created instead of (b) and (c).

(G) When V2≤Vi Vo = Vcc (h) When dVi / dt <0, V1 <Vi≤V2
Vo = Vcc In this way, the redundancy of the rule can be reduced by removing the redundant condition of the rule and changing the condition value.

[0043]

As described above, according to the present invention,
By eliminating redundant conditions in the knowledge base, the redundancy of the knowledge base can be reduced and the individual rule coverage can be broadened. Moreover, the rules in the knowledge base can be kept consistent.

[Brief description of drawings]

FIG. 1 is a block diagram of a knowledge base management apparatus showing an embodiment of the present invention.

FIG. 2 is a block diagram of a knowledge base management apparatus of the present invention.

FIG. 3 is a flowchart showing comparison of rules.

FIG. 4 is a flowchart showing processing of redundancy removal 1;

FIG. 5 is a flowchart showing processing of redundancy removal 2;

FIG. 6 is a flowchart showing a process of removing a contradiction.

FIG. 7 is a block diagram of a knowledge base management apparatus showing another embodiment of the present invention.

FIG. 8 is a diagram showing removal of rule redundancy.

FIG. 9 is a diagram showing a Schmitt trigger circuit.

FIG. 10 is a diagram showing input / output characteristics of a Schmitt trigger circuit.

FIG. 11 is a diagram showing a rule change in the conventional technique.

FIG. 12 is a diagram showing a change in rule in the conventional technique.

FIG. 13 is a diagram showing a change in rule in the conventional technique.

FIG. 14 is a diagram showing a change in rule in the conventional technique.

[Explanation of symbols]

100 ... Knowledge base, 104 ... Knowledge comparing unit, 116 ... Knowledge refining unit, 120 ... New rule.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Masahiro Abe 1-280, Higashi Koikekubo, Kokubunji, Tokyo Inside the Central Research Laboratory, Hitachi, Ltd.

Claims (6)

[Claims] 1. A knowledge base management apparatus having a knowledge base, which is a set of rules having a condition part and a consequent part which is effective when the condition is satisfied, is provided with a condition part between rules in the knowledge base. It has a condition part comparison part that includes a condition value analysis part that analyzes the condition value to be configured, and a knowledge comparison part that includes a consequent part comparison part that compares the consequent part. A knowledge including a condition value changing unit for changing a condition value, a knowledge refining unit for creating a new rule based on a result of changing the condition value, and storing the new rule in a knowledge base. Base management device. 2. A knowledge base management apparatus having a knowledge base, which is a set of rules having a condition part and a consequent part that is effective when the condition is satisfied, in the knowledge base management device, the rules added to the knowledge base, and the knowledge base. For existing rules in, the condition part comparison part that includes the condition value analysis part that analyzes the condition values that form the condition part, and the knowledge comparison part that includes the consequent part comparison part that compares the consequent part Section and consequent section, the result includes a condition value changing section for changing a plurality of condition values, and a knowledge refinement section for creating a new rule based on the result of changing the condition value. A knowledge base management device characterized by storing the information in a knowledge base. 3. A knowledge base management method having a knowledge base, which is a set of rules having a condition part and a consequent part which is effective when the condition is satisfied, in the knowledge base, a condition part is defined between rules in the knowledge base. Analyze the condition values to be composed Analyze the conditions, analyze the consequent parts, change the condition values based on the result of comparing the condition part and the consequent part, create a new rule, A knowledge base management method characterized by storing rules in a knowledge base. 4. A knowledge base management method having a knowledge base, which is a set of rules having a conditional part and a consequent part that is effective when the condition is satisfied, in a rule and a knowledge base added to the knowledge base. For existing rules of
Analyze conditions that analyze the condition values that make up the condition part,
Knowledge characterized by analyzing the consequent parts, changing a plurality of condition values based on the result of comparing the consequent part and the consequent part, creating a new rule, and storing the new rule in a knowledge base Base management method. 5. A knowledge base management method having a knowledge base, which is a set of rules having a conditional part and a consequent part that is effective when the condition is satisfied, in the knowledge base, a conditional part is provided between rules in the knowledge base. A knowledge base management method characterized in that conditions for analyzing constituent conditions are analyzed, consequent parts are analyzed, and a contradiction between rules is detected based on a result of comparison between the condition part and the consequent part. 6. A knowledge base management method having a knowledge base, which is a set of rules having a conditional part and a consequent part which is effective when the condition is satisfied, in a rule added to the knowledge base and in the knowledge base. For existing rules, analyze the condition values that make up the condition part, analyze the conditions, analyze the consequence parts, and detect inconsistencies between the rules based on the results of comparing the condition part and the consequence part. A knowledge base management method characterized by the above.