Continuous-Time Markov Decisions based on Partial Exploration
Systems and Control
2018-07-26 v1 Logic in Computer Science
Abstract
We provide a framework for speeding up algorithms for time-bounded reachability analysis of continuous-time Markov decision processes. The principle is to find a small, but almost equivalent subsystem of the original system and only analyse the subsystem. Candidates for the subsystem are identified through simulations and iteratively enlarged until runs are represented in the subsystem with high enough probability. The framework is thus dual to that of abstraction refinement. We instantiate the framework in several ways with several traditional algorithms and experimentally confirm orders-of-magnitude speed ups in many cases.
Cite
@article{arxiv.1807.09641,
title = {Continuous-Time Markov Decisions based on Partial Exploration},
author = {Pranav Ashok and Yuliya Butkova and Holger Hermanns and Jan Křetínský},
journal= {arXiv preprint arXiv:1807.09641},
year = {2018}
}