Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Abstract. We compare several languages for specifying Markovian population models such as queuing networks and chemical reaction networks. These languages —matrix descriptions, s...
Thomas A. Henzinger, Barbara Jobstmann, Verena Wol...
Model checking is a powerful and widespread technique for the verification of finite distributed systems. However, the main hindrance for wider application of this technique is the...
When enacting a web service orchestration defined using the Business Process Execution Language (BPEL) we observed various safety property violations. This surprised us considerab...
David S. Rosenblum, Howard Foster, Jeff Kramer, Je...