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APRIL: Active Preference-learning based Reinforcement Learning
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Keyword visual representation for interactive image retrieval and image annot...
As regard image retrieval today, we often manipulate large volumes of images, which may vary or even update continuously. In an image database, we end up with both old... -
Sequential approaches for learning datum-wise sparse representations
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Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Out...
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Model-learning actor-critic algorithms: performance evaluation in a motion co...
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Learning to play games in extensive form by valuation
Game theoretic models of learning which are based on the strategic form of the game cannot explain learning in games with large extensive form. We study learning in... -
A survey of actor-critic reinforcement learning: standard and natural policy ...
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Learning a Move-Generator for Upper Con dence Trees
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Off-policy Learning in Large-scale POMDP-based Dialogue Systems
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Dopaminergic control of the exploration-exploitation trade-off via the basal ...
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Robot cognitive control with a neurophysiologically inspired reinforcement le...
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Learning what to say and how to say it: joint optimization of spoken dialogue...
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Interaction with Machine Improvisation
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Finite-Sample Analysis of Least-Squares Policy Iteration
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Learning User Preferences in Ubiquitous Systems: A User Study and a Reinforce...
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Intrinsic Motivation for Autonomous Mental Development
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DS 2012 : Discovery Science
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Interactions between the Midbrain Superior Colliculus and the Basal Ganglia.
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Off-policy Learning with Eligibility Traces: A Survey
In the framework of Markov Decision Processes, off-policy learning, that is the problem of learning a linear approximation of the value function of some fixed policy... -
Adaptative transfer in reinforcement learning : application for simulation of...
A possible way to accelerate reinforcement learning process is to guide the exploration process using prior domain knowledge. This called knowledge transfer, and most...
