3 papers
eess.SY2017
Supervisor Synthesis of POMDP based on Automata Learning
Xiaobin Zhang, Bo Wu, Hai Lin
As a general and thus popular model for autonomous systems, partially observable Markov decision process (POMDP) can capture uncertainties from different sources like sensing noise…
cs.LO2017
Permissive Supervisor Synthesis for Markov Decision Processes through Learning
Bo Wu, Xiaobin Zhang, Hai Lin
This paper considers the permissive supervisor synthesis for probabilistic systems modeled as Markov Decision Processes (MDP). Such systems are prevalent in power grids, transporta…
cs.LO2017
Counterexample-guided Abstraction Refinement for POMDPs
Xiaobin Zhang, Bo Wu, Hai Lin
Partially Observable Markov Decision Process (POMDP) is widely used to model probabilistic behavior for complex systems. Compared with MDPs, POMDP models a system more accurate but…