Results 231 to 240 of about 399,699 (283)
Fluctuation Relations Associated to an Arbitrary Bijection in Path Space. [PDF]
Math Phys Anal GeomChétrite R, Marcantoni S.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Quantile Markov Decision Processes
Operations Research, 2022Title: Sequential Decision Making Using Quantiles The goal of a traditional Markov decision process (MDP) is to maximize the expectation of cumulative reward over a finite or infinite horizon. In many applications, however, a decision maker may be interested in optimizing a specific quantile of the cumulative reward. For example, a physician may want
Xiaocheng Li +2 more
openaire +3 more sources
Statistica Neerlandica, 1985
AbstractA review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the ...
Wal, van der, J., Wessels, J.
openaire +1 more source
AbstractA review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the ...
Wal, van der, J., Wessels, J.
openaire +1 more source
Theory of Probability & Its Applications, 1956
Let $\mathcal{E}$ be a metric space, and suppose that $\mathfrak{B}$ is the Borel field generated by the open sets of $\mathcal{E}$. A stochastic process is defined on $\mathcal{E}$ if a function $x(t,\omega )$$(0 \leqq t < \infty ,\omega \in \Omega )$ and a system of probability measures ${\bf P}_x (x \in \mathcal{E})$ are given such that all ${\bf P ...
Dynkin, E. B., Yushkevich, A. A.
openaire +2 more sources
Let $\mathcal{E}$ be a metric space, and suppose that $\mathfrak{B}$ is the Borel field generated by the open sets of $\mathcal{E}$. A stochastic process is defined on $\mathcal{E}$ if a function $x(t,\omega )$$(0 \leqq t < \infty ,\omega \in \Omega )$ and a system of probability measures ${\bf P}_x (x \in \mathcal{E})$ are given such that all ${\bf P ...
Dynkin, E. B., Yushkevich, A. A.
openaire +2 more sources
SIAM Journal on Applied Mathematics, 1973
A piecewise Markov process is a discrete-state, continuous-parameter stochastic process which is Markovian within contiguous time-segments. Starting at the beginning of a segment in some initial state, the process evolves in a Markovian manner until the segment terminates at a random time whose distribution is completely determined by the initial state.
openaire +2 more sources
A piecewise Markov process is a discrete-state, continuous-parameter stochastic process which is Markovian within contiguous time-segments. Starting at the beginning of a segment in some initial state, the process evolves in a Markovian manner until the segment terminates at a random time whose distribution is completely determined by the initial state.
openaire +2 more sources