Dynamic programming in in uence diagrams with decision circuits
  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.
