Analysis of Probabilistic Basic Parallel Processes [article]

Rémi Bonnet and Stefan Kiefer and Anthony W. Lin
2014 arXiv   pre-print
Basic Parallel Processes (BPPs) are a well-known subclass of Petri Nets. They are the simplest common model of concurrent programs that allows unbounded spawning of processes. In the probabilistic version of BPPs, every process generates other processes according to a probability distribution. We study the decidability and complexity of fundamental qualitative problems over probabilistic BPPs -- in particular reachability with probability 1 of different classes of target sets (e.g.
more » ... sets). Our results concern both the Markov-chain model, where processes are scheduled randomly, and the MDP model, where processes are picked by a scheduler.
arXiv:1401.4130v1 fatcat:b4myall445aiffupcgf7nxlxdq