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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
SIGMOD
2008
ACM
122views Database» more  SIGMOD 2008»
15 years 7 days ago
UQBE: uncertain query by example for web service mashup
The UQBE is a mashup tool for non-programmers that supports query-by-example (QBE) over a schema made up by the user without knowing the schema of the original sources. Based on a...
Jun'ichi Tatemura, Songting Chen, Fenglin Liao, Ol...
ICMLA
2009
14 years 10 months ago
Sensitivity Analysis of POMDP Value Functions
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
Stéphane Ross, Masoumeh T. Izadi, Mark Merc...
ANOR
2006
133views more  ANOR 2006»
15 years 12 days ago
Horizon and stages in applications of stochastic programming in finance
To solve a decision problem under uncertainty via stochastic programming means to choose or to build a suitable stochastic programming model taking into account the nature of the r...
Marida Bertocchi, Vittorio Moriggia, Jitka Dupacov...
AAAI
2011
14 years 10 days ago
Coordinated Multi-Agent Reinforcement Learning in Networked Distributed POMDPs
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
Chongjie Zhang, Victor R. Lesser