# Continuous-Time Markov Decisions based on Partial Exploration

arXiv: https://arxiv.org/abs/1807.09641 · HTML: https://mlsanity.com/paper/1807.09641/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [Under-Approximating Expected Total Rewards in POMDPs](https://mlsanity.com/paper/2201.08772/) (2022)

## Abstract (arXiv)

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.