Research Explorer

Project

Imprecise continuous-time Markov chains
Code
01SC3817
Duration
01 March 2017 → 31 August 2021
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Applied mathematics in specific fields
    • Artificial intelligence
  • Social sciences
    • Cognitive science and intelligent systems
Keywords
stochastic processes imprecise probabilities Markov processes robust probabilistic inference game-theoretic probability martingales
 
Project description

We aim to develop a theoretical framework, and efficient algorithms, for imprecise continuous-time Markov chains. The imprecision relates to the parameters of the model, which need not be specified exactly. This leads
to more robust and reliable results. The motivation stems from the popularity of traditional Markov chains, and from society’s increasing demand for features such as robustness and reliability.