Automatic Rule Set Compilation for Complex Decision Logic
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Solution Overview
Problem
Traditional rule-based systems (RBS) are difficult to develop and maintain, especially for complex applications with numerous conditions and decisions, due to high memory and processing requirements, and are often unsuitable for applications like autonomous driving.
Innovation Solution
The automatic generation of an efficient rule set implementation, which allows for the definition and extension of complex rule sets based on improved knowledge of cause and effect, and automatically generates an efficient implementation of a corresponding rule engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional rule-based systems are used to handle complex applications with large number of conditions and decisions, then the system can express complex decision logic, but the memory and processing requirements become very high
Solution Approach 1:
The patent replaces traditional mechanical rule evaluation mechanisms with a compiled predicate logic system. Instead of executing traditional if-then rules during runtime, the system pre-compiles conditions into efficient predicate representations and uses logical resolution to determine actions, significantly reducing processing overhead and memory requirements while maintaining complex decision capabilities
Solution Approach 2:
The system changes the representation parameters of conditions from traditional boolean expressions to compiled predicate logic forms. This transformation allows the system to efficiently represent and evaluate complex conditions by changing how the data is structured and stored, reducing the memory footprint and improving execution efficiency
2Adaptability or versatility
If traditional rule-based systems are used for complex applications, then the system can implement decision logic, but the systems become difficult to develop and maintain
Solution Approach 1:
The system incorporates automatic code generation capabilities that allow it to self-configure and self-optimize. The rule-based system automatically compiles conditions, generates efficient execution code, and maintains its own structure, reducing the manual development and maintenance effort required by users while preserving complex decision logic capabilities
Data Source
AI summary
Automatically generating a rule set implementation is disclosed. A set of rules is accessed. For each non-const rule in the set of rules, one or more implication directed acyclic graphs (DAGs) are constructed. The non-const rule directly causes at least one external output or at least one external action. The one or more implication DAGs specify rule conditions, including one or more observable rule conditions. Implication DAGs that are constructed for the set of rules are compiled to obtain a compiled result that is configured to evaluate rule conditions associated with the set of rules and determine one or more actions when at least one of the rule conditions evaluates to true. The compiled result is output.


