Bayesian Optimal Control of Markovian Genetic Regulatory Networks Conference Paper uri icon

abstract

  • Finding optimal control policies for Markovian genetic regulatory networks requires that the transition probabilities be known precisely. In practice, due to practical limitations and complex nature of the underlying system, this knowledge may be inaccurate or incomplete. To address this difficulty, we construct an uncertainty set around the true network and define a probability distribution over this set, which reflects our prior knowledge about the underlying system. We take a Bayesian approach and formulate the optimal control policy minimizing the expected infinite-horizon discounted cost relative to this uncertainty class, resulting in an intrinsically robust policy. 2013 IEEE.

name of conference

  • 2013 Asilomar Conference on Signals, Systems and Computers

published proceedings

  • 2013 ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS

author list (cited authors)

  • Yousefi, M. R., & Dougherty, E. R.

citation count

  • 0

complete list of authors

  • Yousefi, Mohammadmahdi R||Dougherty, Edward R

publication date

  • November 2013