Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

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… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
With the emergence of new technology-supported learning environments (e.g., MOOCs, mobile edu games), efficient and effective… Expand
  • figure 1
  • figure 3
  • table I
Is this relevant?
2015
2015
We introduce a model-free algorithm for learning in Markov decision processes with parameterized actions-discrete actions with… Expand
  • figure 1.1
  • figure 2.1
  • figure 2.2
  • figure 2.3
  • figure 2.4
Is this relevant?
2009
2009
Real-world control problems are often modeled as Markov Decision Processes (MDPs) with discrete action spaces to facilitate the… Expand
  • table I
  • table II
  • table III
  • table IV
  • table V
Is this relevant?
2007
2007
This chapter contains sections titled: TD Prediction, Advantages of TD Prediction Methods, Optimality of TD(0), Sarsa: On-Policy… Expand
Is this relevant?
2005
2005
Simulation of Multi-agent Systems.- Smooth Scaling Ahead: Progressive MAS Simulation from Single PCs to Grids.- Agent… Expand
Is this relevant?
2004
2004
We analyzed the performance variation of reinforcement learning algorithms in ambiguous state situations commonly caused by the… Expand
Is this relevant?
1999
1999
Les bolometres sont des detecteurs fonctionnant a tres basse temperature et mesurant l'energie deposee par les effets thermiques… Expand
Is this relevant?
1999
1999
Es presenta un conjunt extraordinari de materials de la cova de la Sarsa (Bocairent), que pertanyia a les primeres campanyes d… Expand
Is this relevant?
Highly Cited
1997
Highly Cited
1997
A key element in the solution of reinforcement learning problems is the value function. The purpose of this function is to… Expand
  • figure 9
  • figure 16
  • figure 23
Is this relevant?
Highly Cited
1995
Highly Cited
1995
On large problems, reinforcement learning systems must use parameterized function approximators such as neural networks in order… Expand
  • figure 3
Is this relevant?