ISBN: 9786131382338 - sarsa: algorithm, markov decision process, reinforcement learning, machine learning (3 resultados)

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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 116 pp. Englisch.…

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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. 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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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -High Quality Content by WIKIPEDIA articles! SARSA(State-Action-Reward-State-Action) is an algorithm for learning a Markovdecision process policy, used in the reinforcement learning area ofmachine learning. It was introduced in the technical note 'OnlineQ-Learning using Connectionist Systems' by Rummery & Niranjan (1994)where the alternative name SARSA was only mentioned as a footnote. Thisname simply reflects the fact that the main function for updating theQ-value depends on the current state of the agent 'S1', the action theagent chooses 'A1', the reward 'R' the agent gets for choosing thisaction, the state 'S2' that the agent will now be in after taking thataction, and finally the next action 'A2' the agent will choose in itsnew state. Taking every letter in the quintuple (st , at , rt+1 , st+1at+1) yields the word SARSA.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. …