State-Action-Reward-State-Action

Known as: Sarsa 
State-Action-Reward-State-Action (SARSA) is an algorithm for learning a Markov decision process policy, used in the reinforcement learning area of… (More)
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Topic mentions per year

Topic mentions per year

1995-2017
0102019952017

Papers overview

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2013
2013
We present a reinforcement learning algorithm based on Dyna-Sarsa that utilizes separate representations of reward and punishment… (More)
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2011
2011
As an important approach to solving complex sequential decision problems, reinforcement learning (RL) has been widely studied in… (More)
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2011
2011
The standard reinforcement learning algorithms have proven to be effective tools for letting an agent learn from its experiences… (More)
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2009
2009
Real-world control problems are often modeled as Markov Decision Processes (MDPs) with discrete action spaces to facilitate the… (More)
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2008
2008
The aim of this paper is to enhance the performance of a reinforcement learning game agent controller, within a dynamic game… (More)
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2008
2008
SARSA is a web tool that can be used to align two or more RNA tertiary structures. The basic idea behind SARSA is that we use the… (More)
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2004
2004
This paper introduces a new approach to visual servoing by learning to perform tasks such as centering. The system uses function… (More)
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Highly Cited
1995
Highly Cited
1995
On large problems, reinforcement learning systems must use parameterized function approximators such as neural networks in order… (More)
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