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» Sequential Decision Making Under Uncertainty
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Publication
151views
13 years 10 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
CONSTRAINTS
2006
70views more  CONSTRAINTS 2006»
14 years 11 months ago
Stochastic Constraint Programming: A Scenario-Based Approach
To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs conta...
Armagan Tarim, Suresh Manandhar, Toby Walsh
SICHERHEIT
2010
14 years 9 months ago
A Fuzzy Model for IT Security Investments
: This paper presents a fuzzy set based decision support model for taking uncertainty into account when making security investment decisions for distributed systems. The proposed m...
Guido Schryen
AAAI
2012
13 years 2 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
ICCD
2006
IEEE
171views Hardware» more  ICCD 2006»
15 years 8 months ago
Stochastic Dynamic Thermal Management: A Markovian Decision-based Approach
This paper proposes a stochastic dynamic thermal management (DTM) technique in high-performance VLSI system with especial attention to the uncertainty in temperature observation. ...
Hwisung Jung, Massoud Pedram