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» Mean-Variance Optimization in Markov Decision Processes
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ATAL
2007
Springer
14 years 1 months ago
A globally optimal algorithm for TTD-MDPs
In this paper, we discuss the use of Targeted Trajectory Distribution Markov Decision Processes (TTD-MDPs)—a variant of MDPs in which the goal is to realize a specified distrib...
Sooraj Bhat, David L. Roberts, Mark J. Nelson, Cha...

Publication
151views
12 years 6 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
ECCV
2004
Springer
14 years 9 months ago
Decision Theoretic Modeling of Human Facial Displays
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
Jesse Hoey, James J. Little
ICANN
2001
Springer
14 years 5 days ago
Market-Based Reinforcement Learning in Partially Observable Worlds
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
EUROPKI
2004
Springer
14 years 1 months ago
A Probabilistic Model for Evaluating the Operational Cost of PKI-based Financial Transactions
The use of PKI in large scale environments suffers some inherent problems concerning the options to adopt for the optimal cost-centered operation of the system. In this paper a Mar...
Agapios N. Platis, Costas Lambrinoudakis, Assimaki...