A grammatical evolution approach to the automatic inference of P systems

P systems are a bio-inspired framework for defining parallel models of computation. Despite their relevance for both theoretical and application scenarios, the design and the identification of P systems remain tedious and demanding tasks, requiring considerable time and expertise. In this work, we try to address these problems by proposing an automated methodology based on grammatical evolution (GE)—an evolutionary computation technique—which does not require any domain knowledge. We consider a setting where observations of successive configurations of a P system are available, and we rely on GE for automatically inferring the P system, i.e., its ruleset. Such approach directly addresses the identification problem, but it can also be employed for automated design, requiring the designer to simply express the configurations of the P system rather than its full ruleset. We assess the practicability of the proposed method on six problems of various difficulties and evaluate its behavior i...