Operations Research
Valuation-based systems for Bayesian decision analysis
Operations Research
Decision making using probabilistic inference methods
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Introduction to Bayesian Networks
Introduction to Bayesian Networks
A graph-theoretic analysis of information value
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Probability Bounds for Goal Directed Queries in Bayesian Networks
IEEE Transactions on Knowledge and Data Engineering
Learning diagnostic policies from examples by systematic search
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Decision-theoretic human-robot communication
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Efficient non-myopic value-of-information computation for influence diagrams
International Journal of Approximate Reasoning
Efficient active fusion for decision-making via VOI approximation
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Optimal testing of structured knowledge
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Integrating learning from examples into the search for diagnostic policies
Journal of Artificial Intelligence Research
Optimal value of information in graphical models
Journal of Artificial Intelligence Research
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Human-robot communication for collaborative decision making - A probabilistic approach
Robotics and Autonomous Systems
Efficient sensor selection for active information fusion
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
A utility-theoretic approach to privacy in online services
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Lazy evaluation of symmetric Bayesian decision problems
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Efficient value of information computation
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Determining the value of information for collaborative multi-agent planning
Autonomous Agents and Multi-Agent Systems
Light at the end of the tunnel: a Monte Carlo approach to computing value of information
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
An exact algorithm for computing the same-decision probability
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
| Hi-index | 0.00 |
We present a method for calculation of myopic value of information in influence diagrams (Howard & Matheson, 1981) based on the strong junction tree framework (Jensen et al., 1994). An influence diagram specifies a certain order of observations and decisions through its structure. This order is reflected in the corresponding junction trees by the order in which the nodes are marginalized. This order of marginalization can be changed by table expansion and use of control structures, and this facilitates for calculating the expected value of information for different information scenarios within the same junction tree. In effect, a strong junction tree with expanded tables may be used for calculating the value of information between several scenarios with different observation-decision order. We compare our method to other methods for calculating the value of information in influence diagrams.