Applying Bayesian Networks for Intelligent Adaptable Printing Systems

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Executive Summary

Bayesian networks are around more than twenty years by now. During the past decade they became quite popular in the scientific community. Researchers from application areas like psychology, biomedicine and finance have applied these techniques successfully. In the area of control engineering however, little progress has been made in the application of Bayesian networks. The authors believe that these techniques are useful for systems that dynamically adapt themselves at run-time to a changing environment, which is usually uncertain. Moreover, there is uncertainty about the underlying physical model of the system, which poses a problem for modelling the system.

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