A graphical parallel process language is described that assists a system designer in visualization of system operation. Visualization is essential when building an operational model to experiment with alternative system operation and architectures and to evaluate design tradeoffs. Such visualization is also essential for the knowledge engineering necessary to implement object oriented, rule based decision making in a simulation program. A Pascal simulation programming system is discussed that has been developed to implement the graphical language and rule based control.
A set of routines is described that assist a programmer in modeling object movement and interactions. Interactions occur when objects move in range or leave range of other objects. Interaction events are rescheduled automatically as objects change vectors. Routines are written in Pascal to take advantage of its dynamic memory allocation capability and minimize memory require ments. An airport simulation demonstrates use of the routines.
Developing rules to classify surface ships and submarines based on noisy features extracted from underwater acoustic signals is difficult and time consuming; indeed, it is difficult to generate decision making rules for any complex system. The Operational Evaluation Modeling (OpEM) Simulation Tool Kit including Expert System Controller and Induction Program, discussed in this paper, greatly mitigates this problem for most complex system simulation projects such as airports, factories, or space defense systems. A theory for inductive learning of decision making rules in cybernetic systems is presented to provide a concise way-of thinking about inductive learning. An OpEM directed graph model is presented that describes operation of a sonar detection and classification system. An OpEM Pascal simulation of this system demonstrates how effective classification rules can be that are induced from simulation generated cases, even with noisy features present. The OpEM induction program is described and innovative features are discussed. Rules generated by the OpEM induction program are compared to rules obtained by Ross Quinlan's ID3 induction program. Performance of the OpEM induction program when noisy features are present is compared with ID3.
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