English

Identifying Optimal Sequential Decisions

Artificial Intelligence 2020-04-28 v1 Statistics Theory Methodology Statistics Theory

Abstract

We consider conditions that allow us to find an optimal strategy for sequential decisions from a given data situation. For the case where all interventions are unconditional (atomic), identifiability has been discussed by Pearl & Robins (1995). We argue here that an optimal strategy must be conditional, i.e. take the information available at each decision point into account. We show that the identification of an optimal sequential decision strategy is more restrictive, in the sense that conditional interventions might not always be identified when atomic interventions are. We further demonstrate that a simple graphical criterion for the identifiability of an optimal strategy can be given.

Keywords

Cite

@article{arxiv.1206.3245,
  title  = {Identifying Optimal Sequential Decisions},
  author = {Philip Dawid and Vanessa Didelez},
  journal= {arXiv preprint arXiv:1206.3245},
  year   = {2020}
}

Comments

Appears in Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI2008)

R2 v1 2026-06-21T21:19:32.959Z