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» Building Relational World Models for Reinforcement Learning
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NIPS
2007
15 years 7 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
167
Voted
WWW
2008
ACM
16 years 6 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...
188
Voted
ICML
2010
IEEE
15 years 6 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
15 years 12 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»
16 years 14 days 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...