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Bellman equation

Known as: Bellman-Equation, Bellman's optimality principle, Policy function 
A Bellman equation, named after its discoverer, Richard Bellman, also known as a dynamic programming equation, is a necessary condition for… 
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Papers overview

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Highly Cited
2015
Highly Cited
2015
In recent years there have been many successes of using deep representations in reinforcement learning. Still, many of these… 
Highly Cited
2014
Highly Cited
2014
In this paper we consider deterministic policy gradient algorithms for reinforcement learning with continuous actions. The… 
Highly Cited
2013
Highly Cited
2013
We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input… 
Highly Cited
2011
Highly Cited
2011
During the last decade, sampling-based path planning algorithms, such as probabilistic roadmaps (PRM) and rapidly exploring… 
Highly Cited
1999
Highly Cited
1999
Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and… 
Highly Cited
1997
Highly Cited
1997
Preface.- Basic notations.- Outline of the main ideas on a model problem.- Continuous viscosity solutions of Hamilton-Jacobi… 
Highly Cited
1997
Highly Cited
1997
Highly Cited
1987
Highly Cited
1987
The authors develop two themes in the theory of incentive schemes. First, one need not always use all of the information… 
Highly Cited
1985
Highly Cited
1985
A new model of consumer behavior is developed using a hybrid of cognitive psychology and microeconomics. The development of the… 
Highly Cited
1982