We present a new algorithm for exactly solving decision-making problems represented as an influence diagram. We do not require the usual assumptions of no forgetting and regularity, which allows us to solve problems with limited information. The algorithm, which implements a sophisticated variable elimination procedure, is empirically shown to outperform a state-of-the-art algorithm in randomly generated problems of up to 150 variables and 10^64 strategies.
|Title of host publication||Advances in Neural Information Processing Systems (NIPS) 24|
|Editors||J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F.C.N. Pereira, K.Q. Weinberger|
|Number of pages||9|
|Publication status||Published - 2011|
Bibliographical note(top 5% papers, spotlight presentation, double-blind peer reviewed by >3 reviewers)
- influence diagrams
Mauá, D. D., & de Campos, C. P. (2011). Solving Decision Problems with Limited Information. In J. Shawe-Taylor, R. S. Zemel, P. Bartlett, F. C. N. Pereira, & K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems (NIPS) 24 (pp. 603-611) http://www.eeecs.qub.ac.uk/~c.decampos/publist/papers/maua2011a.pdf