14. A fuzzy rule system in which a fuzzy inference is achieved based on a fuzzy knowledge stored in a knowledge base storage unit, said fuzzy knowledge including fuzzy rules each described in a format having an IF part and a THEN part, and membership functions defining meanings of propositions described in the IF part and the THEN part, said fuzzy rule acquisition system comprising: fuzzy inference execution means for performing a fuzzy inference for at least one input value by using said fuzzy rules of said fuzzy knowledge stored in said knowledge base storage unit, and obtaining a result of the execution of the fuzzy inference; fuzzy inference storage means for storing the execution result of the fuzzy inference; means for comparing the result of the execution of the fuzzy inference with a teaching value, and obtaining an inference error; means for obtaining errors of said fuzzy rules by referring to at least one of combinations of IF parts of said fuzzy rules, combinations of THEN parts of said fuzzy rules, and both of the combinations of the IF parts and THEN parts of said fuzzy rules using said inference error; fuzzy inference error storage means for storing said obtained errors of said fuzzy rules; contradiction determining means for determining whether a pair of said fuzzy rules are mutually contradictory, based on a pair of errors of corresponding rules of said fuzzy rules stored in said fuzzy inference storage unit; means for modifying a fuzzy rule determines as contradictory by using the errors of said fuzzy rules stored said fuzzy inference error storage unit; means for rewriting said fuzzy rule in said knowledge base storage unit determined as contradictory into said modified fuzzy rule; a fuzzy inference unit for performing a fuzzy inference and delivering an inference output, by using input data and said fuzzy knowledge stored in said knowledge base storage unit; means for obtaining ones of the errors and grades of said propositions based on said inference error by referring to at least one of combinations of IF parts of said fuzzy rules, combinations of THEN parts of said fuzzy rules, and both of the combinations of the IF Darts and THEN parts of said fuzzy rules and storing said at least one in said fuzzy inference storage unit; means for determining that there is a missing fuzzy rule if said contradiction determining means judges that there is no contradiction for all said fuzzy rules, and for generating said missing fuzzy rule as new combinations of said propositions based on ones of the errors and grades of said propositions stored in said fuzzy inference error storage unit; and means for adding said generated missing fuzzy rule to said knowledge base storage unit.
14. A fuzzy rule system in which a fuzzy inference is achieved based on a fuzzy knowledge stored in a knowledge base storage unit, said fuzzy knowledge including fuzzy rules each described in a format having an IF part and a THEN part, and membership functions defining meanings of propositions described in the IF part and the THEN part, said fuzzy rule acquisition system comprising: fuzzy inference execution means for performing a fuzzy inference for at least one input value by using said fuzzy rules of said fuzzy knowledge stored in said knowledge base storage unit, and obtaining a result of the execution of the fuzzy inference; fuzzy inference storage means for storing the execution result of the fuzzy inference; means for comparing the result of the execution of the fuzzy inference with a teaching value, and obtaining an inference error; means for obtaining errors of said fuzzy rules by referring to at least one of combinations of IF parts of said fuzzy rules, combinations of THEN parts of said fuzzy rules, and both of the combinations of the IF parts and THEN parts of said fuzzy rules using said inference error; fuzzy inference error storage means for storing said obtained errors of said fuzzy rules; contradiction determining means for determining whether a pair of said fuzzy rules are mutually contradictory, based on a pair of errors of corresponding rules of said fuzzy rules stored in said fuzzy inference storage unit; means for modifying a fuzzy rule determines as contradictory by using the errors of said fuzzy rules stored said fuzzy inference error storage unit; means for rewriting said fuzzy rule in said knowledge base storage unit determined as contradictory into said modified fuzzy rule; a fuzzy inference unit for performing a fuzzy inference and delivering an inference output, by using input data and said fuzzy knowledge stored in said knowledge base storage unit; means for obtaining ones of the errors and grades of said propositions based on said inference error by referring to at least one of combinations of IF parts of said fuzzy rules, combinations of THEN parts of said fuzzy rules, and both of the combinations of the IF Darts and THEN parts of said fuzzy rules and storing said at least one in said fuzzy inference storage unit; means for determining that there is a missing fuzzy rule if said contradiction determining means judges that there is no contradiction for all said fuzzy rules, and for generating said missing fuzzy rule as new combinations of said propositions based on ones of the errors and grades of said propositions stored in said fuzzy inference error storage unit; and means for adding said generated missing fuzzy rule to said knowledge base storage unit. 15. A fuzzy rule acquisition method according to claim 14, wherein said means for modifying a fuzzy rule modifies the fuzzy rule by changing combinations of IF parts of said fuzzy rules, combinations of THEN pares of said fuzzy rules, or both the combinations IF parts and THEN parts of said fuzzy rules.