Validating MAS Models with Mutation

A key reason for choosing agent-based simulation of a biological system over other kinds of simulation model is the potential for structural as well as behavioral correspondence between the simulation model and the modeled system. This correspondence both demands and makes possible new kinds of model validation. We propose evaluating model fidelity by introducing seeded faults that correspond to known or hypothesized mutations, thus tying software validation to biological mutation analysis. We illustrate with consideration of an agent-based model of carbohydrate oxidation in a cell.