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CORR
2010
Springer
106views Education» more  CORR 2010»
13 years 9 months ago
MDPs with Unawareness
Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...
Joseph Y. Halpern, Nan Rong, Ashutosh Saxena
FUIN
2002
63views more  FUIN 2002»
13 years 9 months ago
Probabilistic Cluster Unfoldings
Abstract. This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, g...
Stefan Haar
JMLR
2002
78views more  JMLR 2002»
13 years 9 months ago
Shallow Parsing using Specialized HMMs
We present a unified technique to solve different shallow parsing tasks as a tagging problem using a Hidden Markov Model-based approach (HMM). This technique consists of the incor...
Antonio Molina, Ferran Pla
ML
2002
ACM
121views Machine Learning» more  ML 2002»
13 years 9 months ago
Near-Optimal Reinforcement Learning in Polynomial Time
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
Michael J. Kearns, Satinder P. Singh
ICML
2010
IEEE
13 years 8 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier