Deterministic and non-deterministic stationary random processes
نویسندگان
چکیده
منابع مشابه
Nonequilibrium Stationary States (Deterministic)
Nonequilibrium stationary states (NESS) describe the state of a mechanical system driven and maintained out of equilibrium by external forces. The external forces can be mechanical or thermodynamical. Examples of mechanical forces are external non-Hamiltonian forces imposed on the system or boundary forcing for example in a shear flow. Thermodynamical forces occur when a system is coupled to se...
متن کاملNon-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making problems in such environments. In recent years, attempts were made to apply methods from reinforcement learning to construct decision support systems for action selection in Markovian environments. Although conventional meth...
متن کاملInteractive Visualization of Non-deterministic Discrete Processes
We describe a method to use non-deterministic state transition graphs as tools for exploration of complex processes. For any interesting process, the full state space will probably be large enough that it cannot be displayed nor explored in its entirety. Therefore we suggest that the visualization process only generate as much of the space as is necessary for the continued exploration. We have ...
متن کاملAn Algebra of Concurrent Non-Deterministic Processes
Cherkasova, L.A., and V.E. Kotov, An algebra of concurrent nondeterminstic processes, Theoretical Computer Science 90 (1991) 151-170. This paper illustrates how early ideas and simple naive concepts of concurrency theory of the 1960s have now turned into complex and subtle problems of modern calculi of concurrent processes. An algebra of finite processes AFP, is discussed as an example of resea...
متن کاملNon-Deterministic Policies In Markovian Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision making problems in such environments. In recent years, attempts were made to apply methods from reinforcement learning to construct adaptive treatment strategies, where a sequence of individualized treatments is learned from clinic...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Arkiv för Matematik
سال: 1950
ISSN: 0004-2080
DOI: 10.1007/bf02590625