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» Identifying Optimal Sequential Decisions
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ATAL
2011
Springer
12 years 10 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
ICPR
2008
IEEE
14 years 11 months ago
A new objective function for sequence labeling
We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
Hisashi Kashima, Yuta Tsuboi
IROS
2009
IEEE
206views Robotics» more  IROS 2009»
14 years 4 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
GECCO
2010
Springer
248views Optimization» more  GECCO 2010»
14 years 1 months ago
Integrating decision space diversity into hypervolume-based multiobjective search
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
Tamara Ulrich, Johannes Bader, Eckart Zitzler
IOR
2011
107views more  IOR 2011»
13 years 5 months ago
Information Collection on a Graph
We derive a knowledge gradient policy for an optimal learning problem on a graph, in which we use sequential measurements to refine Bayesian estimates of individual edge values i...
Ilya O. Ryzhov, Warren B. Powell