Control of probabilistic systems under dynamic, partially known environments with temporal logic specifications
Author(s)Wongpiromsarn, Tichakorn; Frazzoli, Emilio
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We consider the synthesis of control policies for probabilistic systems, modeled by Markov decision processes, operating in partially known environments with temporal logic specifications. The environment is modeled by a set of Markov chains. Each Markov chain describes the behavior of the environment in each mode. The mode of the environment, however, is not known to the system. Two control objectives are considered: maximizing the expected probability and maximizing the worst-case probability that the system satisfies a given specification.
Original manuscript March 6, 2012
DepartmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
Proceedings of the 2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
Institute of Electrical and Electronics Engineers (IEEE)
Wongpiromsarn, Tichakorn, and Emilio Frazzoli. “Control of probabilistic systems under dynamic, partially known environments with temporal logic specifications.” In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 7644-7651. Institute of Electrical and Electronics Engineers, 2012.