Bi-criteria Optimization Problem for Rules and Systems of Rules: Cost Versus Uncertainty (Completeness)
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
Computational Bioscience Research Center (CBRC)
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/653084
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AbstractIn this chapter, we consider algorithms which construct the sets of Pareto optimal points for bi-criteria optimization problems for decision (inhibitory) rules and rule systems relative to a cost function and an uncertainty (completeness) measure. We show how the constructed set of Pareto optimal points can be transformed into the graphs of functions which describe the relationships between the considered cost function and uncertainty (completeness) measure. Computer experiments provide us with examples of trade-off between complexity and accuracy for decision and inhibitory rule systems.
CitationAlsolami F, Azad M, Chikalov I, Moshkov M (2019) Bi-criteria Optimization Problem for Rules and Systems of Rules: Cost Versus Uncertainty (Completeness). Intelligent Systems Reference Library: 225–241. Available: http://dx.doi.org/10.1007/978-3-030-12854-8_14.