Approximate dynamic programming with affine ADDs

Authors:
Scott Sanner;William Uther;Karina Valdivia Delgado
Affiliations:
NICTA and ANU, Canberra, Australia;NICTA and UNSW, Sydney, Australia;University of Sao Paulo, Sao Paulo, Brazil
Venue:
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Year:
2010

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Abstract

The Affin ADD (AADD) is an extension of the Algebraic Decision Diagram (ADD) that compactly represents context-specific, additive and multiplicative structure in functions from a discrete domain to a real-valued range. In this paper, we introduce a novel algorithm for efficientl findin AADD approximations that we use to develop the MADCAP algorithm for AADD-based structured approximate dynamic programming (ADP) with factored MDPs. MADCAP requires less time and space to achieve comparable or better approximate solutions than the current state-of-the-art ADD-based ADP algorithm of APRICODD and can provide approximate solutions for problems with context-specific additive and multiplicative structure on which APRICODD runs out of memory.