Modeling individual's aging within a bacterial population using a pi-calculus paradigm
We propose an aging mechanism which develops in artificial bacterial populations fighting against antibiotic molecules. The mechanism is based on very elementary information gathered by each individual and elementary reactions as well. Though we do not interpret the aging process in strictly biological terms, it appears compliant with recent studies on the field, and physically feasible. The root of the aging mechanism is an adaptation strategy based on a thresholding operation that derives from theoretical results on stochastic monotone games. The methods for implementing it denote their rationale in that they represent a sophisticated dialect of pi-calculus, a widespread computational paradigm for implementing dynamics of massive populations with bipolar reactions,. As a result we may implement processes that explain some typical patterns of the evolution of the immunosystems.