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Reasoning with truth values on compacted fuzzy chained rules.
1Dept. of Electron., Santiago de Compostela Univ.
Summary
This study introduces a novel method for executing fuzzy knowledge bases (FKBs) using rule chaining and forward reasoning. The approach enables efficient computation by performing operations a priori, saving significant processing time.
Area of Science:
- Computer Science
- Artificial Intelligence
- Fuzzy Logic
Background:
- Fuzzy knowledge bases (FKBs) require efficient execution methods for rule chaining.
- Existing inference processes can be complex and dependent on specific variable universes of discourse.
Purpose of the Study:
- To develop a method for executing FKBs independent of variable universes of discourse.
- To enable homogeneous treatment of variables within FKBs.
- To optimize computation time for rule chaining in FKBs.
Main Methods:
- Utilizing forward reasoning functions derived from the compositional rule of inference.
- Interpreting rule execution as the propagation of linguistic truth values.
- Analyzing the process in control systems and expert systems applications.
Main Results:
- The proposed method allows rule execution in the truth space, independent of variable definitions.
- A compaction mechanism is presented for a priori operation execution.
- Significant computation time savings are achieved.
Conclusions:
- The developed method provides an efficient and homogeneous approach to executing fuzzy knowledge bases.
- The compaction mechanism offers practical advantages in terms of computational efficiency for control and expert systems.
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