SARSA : Algorithm, Markov Decision Process, Reinforcement Learning, Machine Learning

Language: English

Published by Omniscriptum, 2026

6131382336 / 9786131382338

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Item description from seller

nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! SARSA (State-Action-Reward-State-Action) is an algorithm for learning a Markov decision process policy, used in the reinforcement learning area of machine learning. It was introduced in the technical note 'Online Q-Learning using Connectionist Systems' by Rummery & Niranjan (1994) where the alternative name SARSA was only mentioned as a footnote. This name simply reflects the fact that the main function for updating the Q-value depends on the current state of the agent 'S1', the action the agent chooses 'A1', the reward 'R' the agent gets for choosing this action, the state 'S2' that the agent will now be in after taking that action, and finally the next action 'A2' the agent will choose in its new state. Taking every letter in the quintuple (st , at , rt+1 , st+1 , at+1) yields the word SARSA.

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Bibliographic details

Title
SARSA : Algorithm, Markov Decision Process, Reinforcement Learning, Machine Learning
Author
Lambert M. Surhone
Publisher
Omniscriptum
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6131382336
ISBN 13
9786131382338
Item weight
191 grams
Dimensions
220x150x7 mm

AHA-BUCH GmbH

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Shipping rates from Germany to U.S.A.

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