High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models often requires the generatio...
Gianfranco Ciardo, Joshua Gluckman, David M. Nicol
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
We study distributed state space generation on a cluster of workstations. It is explained why state space partitioning by a global hash function is problematic when states contain...
Stefan Blom, Bert Lisser, Jaco van de Pol, Michael...
Conventional methods for state space exploration are limited to the analysis of small systems because they suffer from excessive memory and computational requirements. We have dev...
William J. Knottenbelt, Peter G. Harrison, Mark Me...