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NIPS
2001
13 years 11 months ago
Reinforcement Learning with Long Short-Term Memory
This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage learning and directed exploration can...
Bram Bakker
NIPS
2001
13 years 11 months ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Gregory Z. Grudic, Lyle H. Ungar
BROADNETS
2007
IEEE
14 years 1 months ago
Reinforcement learning based routing in all-optical networks with physical impairments
Abstract-- We present and evaluate a reinforcement learningbased RWA algorithm for all-optical networks subject to physical impairments. The technique is suitable for decentralized...
Yvan Pointurier, Fariba Heidari
ICML
2009
IEEE
14 years 10 months ago
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning
The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an ...
Carlos Diuk, Lihong Li, Bethany R. Leffler

Book
796views
15 years 8 months ago
Introduction to Machine Learning
This is an introductory book about machine learning. Notice that this is a draft book. It may contain typos, mistakes, etc. The book covers the following topics: Boolean Functio...
Nils J. Nilsson