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AIPS
2000
14 years 11 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
14 years 10 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»
14 years 11 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»
12 years 12 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
14 years 10 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