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AAAI
2012
11 years 9 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»
13 years 6 months 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
13 years 4 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»
13 years 6 months 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
12 years 6 months 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