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190 629 (0,197s)

Result

On the Total Reward Variance for Continuous-Time Markov Reward Chains

As an extension of the discrete-time case, this note investigates the variance of the total cumulative reward for continuous-time Markov reward chains with finite state spaces. The result...

BB - Aplikovaná statistika, operační výzkum

  • 2006
  • Jx
Result

Total reward variance in discrete and continuous time Markov chains

This note studies the variance of total cumulative rewards for Markov reward chains in both discrete and continuous time. It is shown that parallel results can finite time. Next, the infi...

BB - Aplikovaná statistika, operační výzkum

  • 2005
  • D
Result

Second Order Optimality in Markov and Semi-Markov Decision Processes

Semi-Markov decision processes can be considered as an extension of discrete- and continuous-time Markov reward models. Unfortunately, traditional optimality criteria as long-run average reward ...

Statistics and probability

  • 2019
  • D
Result

Markov decision chains in discrete- and continuous-time; a unified approach

In this note we consider Markov decision chains with finite state space in discrete- and continuous-time setting for discounting and averaging optimality criteria. Connections between discounted and averaging optim...

AH - Ekonomie

  • 2010
  • D
Result

Central Moments and Risk-Sensitive Optimality in Continuous-Time Markov Reward Processes

In this note we consider continuous-time Markov decision processes with finite state space where the stream of rewards generated by the Markov processes by the Markov reward process along...

Statistics and probability

  • 2020
  • O
Result

Perturbations and Error Bounds in Discounted Markov Reward Models

This note presents succinct proofs of the basic perturbation formulas for the steady state distributions of finite state discrete-time Markov chains. Perturbation results are then applied to Markov reward ...

BB - Aplikovaná statistika, operační výzkum

  • 2007
  • D
Result

Risk Sensitive Discrete- and Continuous -Time Markov Reward Processes

In this note we consider risk sensitive Markov reward processes with finite state space in discrete- and continuous-time setting. Explicit formulas for the growth rate and average reward optimality are obt...

BC - Teorie a systémy řízení

  • 2008
  • D
Result

Some remarks on the variance in Markov chains with rewards.

We consider a discrete time Markov reward process with finite state space and assume that the rewards associated with the transitions are random variables are interested in properties of cumulative reward ...

BB - Aplikovaná statistika, operační výzkum

  • 2002
  • D
Result

On mean reward variance in semi-Markov processes

As an extension of the discrete-time case, this note investigates the variance of the total cumulative reward for the embedded Markov chain of semi-Markov processes. Under the assumption that the chain...

BB - Aplikovaná statistika, operační výzkum

  • 2005
  • Jx
Result

Risk-sensitive and Mean Variance Optimality in Continuous-time Markov Decision Chains

In this note we consider continuous-time Markov decision processes with finite state and actions spaces where the stream of rewards generated by the Markov zero (risk-neutral case) we arrive at a standard ...

Economic Theory

  • 2018
  • D
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