Solving decision problems with limited information

Denis D. Mauá; Cassio P. de Campos

Solving decision problems with limited information

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

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.

Original language	English
Title of host publication	Proceedings of 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011
Pages	603-611
Number of pages	9
Publication status	Published - 1 Dec 2011
Externally published	Yes
Event	25th Annual Conference on Neural Information Processing Systems, NIPS 2011 - Granada, Spain Duration: 12 Dec 2011 → 14 Dec 2011 Conference number: 25

Publication series

Name	Advances in Neural Information Processing Systems
Volume	24

Conference

Conference	25th Annual Conference on Neural Information Processing Systems, NIPS 2011
Abbreviated title	NIPS 2011
Country/Territory	Spain
City	Granada
Period	12/12/11 → 14/12/11

Bibliographical note

(spotlight presentation, double-blind peer reviewed by >3 reviewers)

Keywords

influence diagrams

Cite this

@inproceedings{07f19e3c86754ebca96abc03dbb693bb,

title = "Solving decision problems with limited information",

abstract = "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.",

keywords = "influence diagrams",

author = "Mau{\'a}, {Denis D.} and {de Campos}, {Cassio P.}",

note = "(spotlight presentation, double-blind peer reviewed by >3 reviewers); 25th Annual Conference on Neural Information Processing Systems, NIPS 2011, NIPS 2011 ; Conference date: 12-12-2011 Through 14-12-2011",

year = "2011",

month = dec,

day = "1",

language = "English",

isbn = "9781618395993",

series = "Advances in Neural Information Processing Systems",

pages = "603--611",

booktitle = "Proceedings of 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011",

}

Solving decision problems with limited information. / Mauá, Denis D.; de Campos, Cassio P.
Proceedings of 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011. 2011. p. 603-611 (Advances in Neural Information Processing Systems; Vol. 24).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

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AU - Mauá, Denis D.

AU - de Campos, Cassio P.

N1 - Conference code: 25

PY - 2011/12/1

Y1 - 2011/12/1

N2 - 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.

AB - 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.

KW - influence diagrams

UR - http://www.scopus.com/inward/record.url?scp=84860648726&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781618395993

T3 - Advances in Neural Information Processing Systems

SP - 603

EP - 611

BT - Proceedings of 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

T2 - 25th Annual Conference on Neural Information Processing Systems, NIPS 2011

Y2 - 12 December 2011 through 14 December 2011

ER -

Solving decision problems with limited information

Abstract

Publication series

Conference

Bibliographical note

Keywords

Other files and links

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Cite this