Discrete Markov process interpretation of propositional logic
Vassil Sgurev, Vladimir Jotsov · 2010
A stochastic interpretation of propositional logic formulas is introduced that uses a specific discrete Markov process with two states. The requirements for this interpretation are formulated. It is shown that the obtained from it stochastic distributions are compatible on a qualitative (probabilistic) level with the respective results of the propositional logic. Examples are presented for usage of this class of Markov processes and the ways for applying it in artificial intelligence, intelligent systems, expert systems are marked.