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AIPS
2000
13 years 6 months ago
A New Perspective on Algorithms for Optimizing Policies under Uncertainty
The paper takes a fresh look at algorithms for maximizing expected utility over a set of policies, that is, a set of possible ways of reacting to observations about an uncertain s...
Rina Dechter
UAI
1998
13 years 6 months ago
An Anytime Algorithm for Decision Making under Uncertainty
We present an anytime algorithm which computes policies for decision problems represented as multi-stage influence diagrams. Our algorithm constructs policies incrementally, start...
Michael C. Horsch, David Poole
RSS
2007
176views Robotics» more  RSS 2007»
13 years 6 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
SIGMETRICS
2012
ACM
248views Hardware» more  SIGMETRICS 2012»
11 years 7 months ago
Pricing cloud bandwidth reservations under demand uncertainty
In a public cloud, bandwidth is traditionally priced in a pay-asyou-go model. Reflecting the recent trend of augmenting cloud computing with bandwidth guarantees, we consider a n...
Di Niu, Chen Feng, Baochun Li
AAAI
1996
13 years 6 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole