Conquering Uncertainty in Multiple-Valued Logic Design
Artificial Intelligence Review
Conquering uncertainty in multiple-valued logic design
Artificial intelligence in logic design
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This paper addresses a new information theoretic approach to minimization of polynomial expressions for Multiple Valued Logic (MVL) functions. Its focus is to determine the so-called pseudo Reed-Muller and pseudo Kronecker expressions of MVL functions. A key point of our approach is the use of information theoretic measures for efficient design of Decision Trees (DTs) to represent MVL functions. We utilize free pseudo Reed-Muller GF(4) (PSDRMGF) DTs and free pseudo Kronecker GF(4) (PSDKGF) DTs. Furthermore, we show that the suggested approach allows to manage the process of minimization in a simple way, for the most of known forms of logic function representation. Our program, Info-MV, produces, in most cases, the extremely better results, in contrast to some known heuristic minimization strategies.