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OPTIMIZATION OF THE SEQUENCE OF LOGICAL INFERENCE STEPS DURING ITS AUTOMATION
Abstract
When we carry out inference automation, the time required to complete the inference procedure is very important. The shorter the time, the more effective the procedure. If we carry out the logical inference procedure manually, then we make a choice of a sequence of steps. In this case, the person takes into account the specifics of the problem being solved. It does not act formally, but taking into account the substantial meaning of predicates. If we are going to shift the inference procedure to a computer, then we need to develop an algorithm that will determine the sequence of inference steps. In this case, the specifics of the problem or the meaning of predicates cannot be taken into account. The algorithm must be universal and act formally. Obviously, this algorithm may not be the best for any task. However, it is necessary to lay in it the principles of choosing the next step, which will make it better for any tasks. A good choice of the next step in the logical inference sequence can significantly increase the efficiency of the algorithm. On the other hand, an unsuccessful step can lead to an exponential increase in the number of possible alternatives in the next step. In this paper, we propose some principles that must be followed when creating an efficiency criterion when choosing the next logical inference step. Based on this criterion, taking into account the priority of the principles, performance evaluations for alternatives are built. Based on the estimates obtained, a specific action is selected at the next step of the logical inference. The application of the proposed estimates made it possible to significantly improve the operation of the inference algorithm on problems from real practice, when compared with ordering the steps of inference without applying these estimates.
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