XPS: Backward Chaining RulesBackward Chaining Rules define how values for DESCRIPTORs are derived from values of other DESCRIPTORs, user inputs, simulation model results or other information available (data bases, GIS, etc.).
RULES are associated with Descriptors, and/or referenced by other RULES.
RULES that set (assign a value) to a (target) DESCRIPTOR, are listed with that DESCRIPTOR as target Rules DESCRIPTORS that are used in the condition part of any other RULE may in turn have Target RULES defined, that will be triggered as part of the backward chaining inference model.
RULE <rule#> IF <condition> THEN <action> ENDRULE <condition> := <condition <logical operator> <condition> := descriptor <comparative operator> <operand> := descriptor <singular operator> := TRUE <action> := descriptor = <operand> := descriptor <meta operator> <constant> <operand> := <operand> <arithmetic operator> <operand> := descriptor := <constant> <logical operator> := AND | OR <comparative operator> := < | > | <= | >= | == | != <singular operator> := EXISTS | NOT_EXISTS <arithmetic operator> := [ | ] | * | / | + | - <meta operator> := INCREASES_BY | DECREASES_BY := BECOMES <constant> := string := number
Rules can result in the absolute assignment of DESCRIPTOR values, their relative, incremental modification, or they can be used to control the inference strategy depending on context. Rules can also include simple formulas; more complex functions can be used through the generic model interface.
An example for a rule used in the reservoir expert system is:
RULE 1020231 IF average_reservoir_depth == small AND retention_time < 30 THEN reservoir_stratification = unlikely ENDRULE
Also, the user can call up a knowledge base browser, that allows to navigate in the tree structure of the knowledge base within the context of individual problems. The browser can descend the inference tree, displaying sets of rules referring to a list of DESCRIPTORs and allow to inspect individual DESCRIPTOR definitions.
The possibility to integrate models in place of rules in an expert system and at the same time use embedded rule-based components in models provides a very rich repertoire of building blocks for interactive software systems.
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