This book begins the task of defining, explaining, arguing for, and, in the end, providing a rationale for information processing. Volume I is concerned with the notion that an information processor is mainly engaged in making inferences. An information processor would prefer to reach definite conclusions by using some form of deduction. Unfortunately, it is often thwarted in this desire by a fundamental lack of relevant information. Probability theory has developed as a rigorous way of dealing with the uncertainty surrounding inference. Thus, we begin by treating some of the formal manipulation rules that crop up in probability theory. To provide some foundational basis for the applications to appear in later Volumes, the topics of Boolean Algebra, Classical Logic, and Cellular Automata will make an appearance here.