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1995, 1, Pitman research notes in mathematics series, ISBN 0582273706, Volume 327, 134
The conjugate gradient method is a powerful tool for the iterative solution of self-adjoint operator equations in Hilbert space.This volume summarizes and... 
Improperly posed problems | Conjugate gradient methods | Numerical analysis | Applied Mathematics | Differential Equations | Mathematical Analysis | Numerical analysis-Improperly posed problems
Book
Journal Article
Neural networks, ISSN 0893-6080, 05/2010, Volume 23, Issue 4, pp. 551 - 559
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling... 
Policy gradients | Control | Stochastic optimisation | Robotics | Reinforcement learning | Markov Chains | Algorithms | Artificial Intelligence | Computer Simulation | Decision Support Techniques | Reinforcement (Psychology) | Models, Statistical | Neural Networks (Computer) | Analysis | Robots | Index Medicus
Journal Article
Neurocomputing (Amsterdam), ISSN 0925-2312, 03/2008, Volume 71, Issue 7-9, pp. 1180 - 1190
In this paper, we suggest a novel reinforcement learning architecture, the Natural Actor-Critic. The actor updates are achieved using stochastic policy... 
Actor-Critic methods | Policy-gradient methods | Robot learning | Natural gradients | Reinforcement learning | Compatible function approximation | Analysis | Algorithms
Journal Article