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IJAR
2006
98views more  IJAR 2006»
13 years 7 months ago
A forward-backward Monte Carlo method for solving influence diagrams
Although influence diagrams are powerful tools for representing and solving complex decisionmaking problems, their evaluation may require an enormous computational effort and this...
Andrés Cano, Manuel Gómez, Seraf&iac...
ATAL
2007
Springer
13 years 11 months ago
Interactive dynamic influence diagrams
This paper extends the framework of dynamic influence diagrams (DIDs) to the multi-agent setting. DIDs are computational representations of the Partially Observable Markov Decisio...
Kyle Polich, Piotr J. Gmytrasiewicz
JAIR
2008
138views more  JAIR 2008»
13 years 7 months ago
Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and Decision-Making Processes
This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents' beliefs and decision-making processes....
Ya'akov Gal, Avi Pfeffer
IJCAI
2001
13 years 8 months ago
Multi-Agent Influence Diagrams for Representing and Solving Games
The traditional representations of games using the extensive form or the strategic (normal) form obscure much of the structure that is present in real-world games. In this paper, ...
Daphne Koller, Brian Milch
ATAL
2009
Springer
13 years 11 months ago
Improved approximation of interactive dynamic influence diagrams using discriminative model updates
Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs fac...
Prashant Doshi, Yifeng Zeng