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» Ranking policies in discrete Markov decision processes
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ATAL
2011
Springer
12 years 8 months ago
Towards a unifying characterization for quantifying weak coupling in dec-POMDPs
Researchers in the field of multiagent sequential decision making have commonly used the terms “weakly-coupled” and “loosely-coupled” to qualitatively classify problems i...
Stefan J. Witwicki, Edmund H. Durfee
CN
2004
138views more  CN 2004»
13 years 7 months ago
Performance evaluation of prioritized scheduling with buffer management for differentiated services architectures
Differentiated services (DiffServ) is an architecture for the Internet in which various applications are supported using a simple classification scheme. Packets entering the DiffS...
Ahmed E. Kamal, Hossam S. Hassanein
LION
2007
Springer
192views Optimization» more  LION 2007»
14 years 2 months ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto
NIPS
1998
13 years 9 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
AAAI
2012
11 years 10 months ago
A Dynamic Rationalization of Distance Rationalizability
Distance rationalizability is an intuitive paradigm for developing and studying voting rules: given a notion of consensus and a distance function on preference profiles, a ration...
Craig Boutilier, Ariel D. Procaccia