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Important to the performance of interactive systems is the ability of its members to associate current knowledge with knowledge of past experience. Knowledge association discussed here results in greater detail of a current knowledge and is demonstrated through the use of examples. It is based on knowledge about automata and the knowledge structures are in the form of graphs.

Part I, presented in the preceding issue of Kybernetes, concluded with the analysis for establishing the normal sequences for the principal statements of a general logical discourse. Part II continues with an analyses for establishing the different types of sequences, the normal sequences for the secondary statements, the review sequences, and the repeat sequences. An analysis is presented for establishing the primitives that define a sequence graph for a general logical discourse, and the use of the primitives is demonstrated in the construction of a sequence graph for an example logical discourse. Finally, there are presented various plans for interaction between man and machine for the transfer of knowledge of a logical discourse and the application of the algorithm to the structuring of knowledge for a common discourse.

Important to the performance of intelligent systems is the ability of its members to deduce conclusions as responses from premisses received as knowledge during different time periods. Two types of knowledge associations are established for combing knowledge structures received during different time periods into fewer coherent structures. The knowledge system used has the graphs for a general automaton as a formal way of storing knowledge in a computer. Basic types of arguments arising from the natural deductive processes are identified and established as valid through the procedures for formal logic.

A mathematical analysis is made of a general logical discourse for the purpose of achieving a transfer of knowledge for any logical discourse from computer to man. There results an algorithm for structuring any logical discourse and a basis for the design of plans of interaction. In Part I, an analysis is made of a general logical discourse for establishing the sets and relations for the knowledge statements, for establishing the primitives that define a prerequisite graph, and for establishing the normal sequences for the principal statements. The use of the primitives is demonstrated in the construction of a prerequisite graph for an example logical discourse. In Part II (appearing in a subsequent issue) the analysis is continued for establishing other sequences, the primitives for a sequence graph, various plans for interaction, and the application to a common discourse.

Part I, presented in the preceding issue of Kybernetes, concluded with the presentation of a theorem in the form of an algorithm to aid in the modeling of the inherited ability of an automaton to modify and extend its knowledge structures. Part II continues with the presentation of the proof of the theorem, and the theorem is applied to a case study to determine the states of an automaton when the states could not be observed during a period of performance. The application of the disciplines of the General Systems Theory is further indicated for a second case study of an industrial system of 10 interactive automata.

Select properties are presented for a graph model of a general automaton consisting of a processor, environment and time graph. The properties, stated in the form of theorems and corollaries, deal with connectedness, number of points and lines and indegree and outdegree as the model relates to the automaton's sets, functions and characteristics. The properties are illustrated by an example automaton.

Important to the performance of interactive systems is the ability of its members to establish valid arguments. The type of arguments discussed here contains a premiss of form A of the Aristotelian logic, a second premiss and the conclusion, and the deductive process involves the predicate logic. Knowledge structures for storing the meanings of the arguments are based on principles for general automata and are in the form of graphs. After recognizing the knowledge structures for the premisses by a computer, determining conclusions and storing the meanings of the conclusions become a standard procedure.

Artificial automata replace, in part or in total, natural automata in systems, and properly disciplined models of natural automata become design models of artificial automata for replacement. In Part I, a summary of two sets of disciplines provided by a General Systems Theory is presented, and the importance of these disciplines to the modeling of three inherited abilities is indicated for a case study. A theorem is presented in the form of an algorithm to aid in the modeling of the ability to modify and extend knowledge structures. In Part II (appearing in the next issue), the proof of the theorem is given and the theorem is applied to the case study. Finally, the application of the disciplines of the General Systems Theory is indicated for a second casestudy of an industrial system of 10 interactive automata.