Dynamic programming in in uence diagrams with decision circuits
Artificial Intelligence
2012-03-19 v1
Abstract
Decision circuits perform efficient evaluation of influence diagrams, building on the ad- vances in arithmetic circuits for belief net- work inference [Darwiche, 2003; Bhattachar- jya and Shachter, 2007]. We show how even more compact decision circuits can be con- structed for dynamic programming in influ- ence diagrams with separable value functions and conditionally independent subproblems. Once a decision circuit has been constructed based on the diagram's "global" graphical structure, it can be compiled to exploit "lo- cal" structure for efficient evaluation and sen- sitivity analysis.
Cite
@article{arxiv.1203.3513,
title = {Dynamic programming in in uence diagrams with decision circuits},
author = {Ross D. Shachter and Debarun Bhattacharjya},
journal= {arXiv preprint arXiv:1203.3513},
year = {2012}
}
Comments
Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)