Rollout algorithms: an overview

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

We review recent progress and open issues in the approximate solution of deterministic and stochastic optimization problems using rollout algorithms. These algorithms start with a heuristic policy and try to improve on that policy using on-line learning and simulation. They are related to dynamic programming and they are based on policy iteration ideas. Their attractive aspects are simplicity, broad applicability, and suitability for on-line implementation. While they do not aspire to optimal performance, rollout algorithms typically result in a consistent and substantial improvement over the underlying heuristic.

Original languageEnglish (US)
Pages (from-to)448-449
Number of pages2
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - 1999
Externally publishedYes
EventThe 38th IEEE Conference on Decision and Control (CDC) - Phoenix, AZ, USA
Duration: Dec 7 1999Dec 10 1999

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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