Systematic constraint satisfaction

For each experiment, the true values of the measured variables are related by one or more constraints. Because the number of data points exceeds the number of parameters to be estimated, all constraint equations are not exactly satisfied for all experimental measurements. Exact agreement between theory and experiment is not achieved due to random and systematic errors in the data and to "lack of fit" of the model to the data. Optimum parameters and true values corresponding to the experimental measurements must be found by satisfaction of an appropriate statistical criterion. 

Given a fixed, predetermined set of elementary reactions, compose reaction pathways (mechanisms) that satisfy given specifications in the transformation of available raw materials to desired products. This is a problem encountered quite frequently during research and development of chemical and biochemical processes. As in the assembly of a puzzle, the pieces (available reaction steps) must fit with each other (i.e., satisfy a set of constraints imposed by the precursor and successor reactions) and conform with the size and shape of the board (i.e., the specifications on the overall transformation of raw materials to products). This chapter draws from symbolic and quantitative reasoning ideas of AI which allow the systematic synthesis of artifacts through a recursive satisfaction of constraints imposed on the artifact as a whole and on its components. The artifacts in this chapter are mechanisms of catalytic reactions and... 

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