Adaptive Aggregation Methods for Infinite Horizon Dynamic Programming

Dimitri P. Bertsekas, David A. Castanon

Research output: Contribution to journalArticlepeer-review

108 Scopus citations


We propose a class of iterative aggregation algorithms for solving infinite horizon dynamic programming problems. The idea is to interject aggregation iterations in the course of the usual successive approximation method. An important new feature that sets our method apart from earlier proposals is that the aggregate groups of states change adaptively from one aggregation iteration to the next, depending on the progress of the computation. This allows acceleration of convergence in difficult problems involving multiple ergodic classes for which methods using fixed groups of aggregate states are ineffective. No knowledge of special problem structure is utilized by the algorithms.

Original languageEnglish (US)
Pages (from-to)589-598
Number of pages10
JournalIEEE Transactions on Automatic Control
Issue number6
StatePublished - Jun 1989
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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