On Stochastic Rewriting and Combinatorics via Rule-Algebraic Methods


Building upon the rule-algebraic stochastic mechanics framework, we present new results on the relationship of stochastic rewriting systems described in terms of continuous-time Markov chains, their embedded discrete-time Markov chains and certain types of generating function expressions in combinatorics. We introduce a number of generating function techniques that permit a novel form of static analysis for rewriting systems based upon marginalizing distributions over the states of the rewriting systems via pattern-counting observables.

Invited Paper in Patrick Bahr (ed.): Proceedings 11th International Workshop on Computing with Terms and Graphs (TERMGRAPH 2020), Online, 5th July 2020, Electronic Proceedings in Theoretical Computer Science 334, pp. 11–28.