Use of Bit-masking in Content-Functional Intelligent System Control

G.N. Pitts, J.P. Myers, Jr., A.D. Brock, and K.B. Landrum (USA)


Artificial Intelligence, Control, Real-Time Monitoring, Robotic Systems.


Historically, artificial intelligence has faced two major problems in its evolution, those of speed and storage space. The research presented in this paper provides a possible solution to these problems by utilizing a new technique for decision making in AI. By mapping input data to appropriate bit patterns and creating a structure through which the data flows based on the results of various AND and OR masking operations, the data itself becomes content functional. In this context, content functional means that the data itself contains all the necessary information about what it is, where it goes and what to do with it when it gets there. The focus of this research is to develop a set of algorithms that take expert information regarding input data, critical situations and their corresponding actions to create a masking structure that can be easily navigated through via the aforemen tioned methods. This process eliminates the need for great quantities of textual information and their myriad of relationships, thereby helping to solve the problem of insufficient storage space. In addition, the use of native operations on data at the bit level significantly increases the speed at which information can be processed.

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