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» Building Relational World Models for Reinforcement Learning
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NIPS
2007
13 years 9 months ago
Online Linear Regression and Its Application to Model-Based Reinforcement Learning
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
Alexander L. Strehl, Michael L. Littman
WWW
2008
ACM
14 years 8 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
ICML
2010
IEEE
13 years 8 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint
KES
2007
Springer
14 years 1 months ago
Making Financial Trading by Recurrent Reinforcement Learning
In this paper we propose a financial trading system whose strategy is developed by means of an artificial neural network approach based on a recurrent reinforcement learning algo...
Francesco Bertoluzzo, Marco Corazza
ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
14 years 2 months ago
Model-based and model-free reinforcement learning for visual servoing
— To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by b...
Amir Massoud Farahmand, Azad Shademan, Martin J&au...