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Discrete Event Modeling and Simulation of Markov Decision Process.: Application to the Leverage Effects in Financial Asset Optimization Processes. - Softcover
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Markov Decision Process (MDP) models are widely used to model decision-making problems in many research fields. MDPs can be readily designed through modeling and simulation(M&S) using the Discrete Event System Specification formalism (DEVS) due to its modular and hierarchical aspects, which improve the explainability of the models. In particular, the separation between the agent and the environment components involved in the traditional reinforcement learning (RL) algorithm, such as Q-Learning, is clearly formalized to enhance observability and envision the integration of AI components in the decision-making process. Our proposed DEVS model also improves the trust of decision makers by mitigating the risk of delegation to machines in decision-making processes. The main focus of this work is to provide the possibility of designing a Markovian system with a modeling and simulation formalism to optimize a decision-making process with greater explainability through simulation. Furthermore, the work involves an investigation based on financial process management, its specification as an MDP-based RL system, and its M&S with DEVS formalism.
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Discrete Event Modeling and Simulation of Markov Decision Process.
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LAP Lambert Academic Publishing, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Markov Decision Process (MDP) models are widely used to model decision-making problems in many research fields. MDPs can be readily designed through modeling and simulation(M&S) using the Discrete Event System Specification formalism (DEVS) due to its modul. Seller Inventory # 1294647999
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Discrete Event Modeling and Simulation of Markov Decision Process.
Published by
LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Markov Decision Process (MDP) models are widely used to model decision-making problems in many research fields. MDPs can be readily designed through modeling and simulation(M&S) using the Discrete Event System Specification formalism (DEVS) due to its modular and hierarchical aspects, which improve the explainability of the models. In particular, the separation between the agent and the environment components involved in the traditional reinforcement learning (RL) algorithm, such as Q-Learning, is clearly formalized to enhance observability and envision the integration of AI components in the decision-making process. Our proposed DEVS model also improves the trust of decision makers by mitigating the risk of delegation to machines in decision-making processes. The main focus of this work is to provide the possibility of designing a Markovian system with a modeling and simulation formalism to optimize a decision-making process with greater explainability through simulation. Furthermore, the work involves an investigation based on financial process management, its specification as an MDP-based RL system, and its M&S with DEVS formalism. 168 pp. Englisch. Seller Inventory # 9786206846697
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Discrete Event Modeling and Simulation of Markov Decision Process.
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
New
Softcover
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Discrete Event Modeling and Simulation of Markov Decision Process.
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LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
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Discrete Event Modeling and Simulation of Markov Decision Process. : Application to the Leverage Effects in Financial Asset Optimization Processes.
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
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Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Markov Decision Process (MDP) models are widely used to model decision-making problems in many research fields. MDPs can be readily designed through modeling and simulation(M&S) using the Discrete Event System Specification formalism (DEVS) due to its modular and hierarchical aspects, which improve the explainability of the models. In particular, the separation between the agent and the environment components involved in the traditional reinforcement learning (RL) algorithm, such as Q-Learning, is clearly formalized to enhance observability and envision the integration of AI components in the decision-making process. Our proposed DEVS model also improves the trust of decision makers by mitigating the risk of delegation to machines in decision-making processes. The main focus of this work is to provide the possibility of designing a Markovian system with a modeling and simulation formalism to optimize a decision-making process with greater explainability through simulation. Furthermore, the work involves an investigation based on financial process management, its specification as an MDP-based RL system, and its M&S with DEVS formalism. Seller Inventory # 9786206846697
Quantity: 1 available
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Discrete Event Modeling and Simulation of Markov Decision Process.
Published by
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
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Softcover
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Discrete Event Modeling and Simulation of Markov Decision Process.
Published by
LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6206846695
ISBN 13: 9786206846697
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. Neuware -Markov Decision Process (MDP) models are widely used to model decision-making problems in many research fields. MDPs can be readily designed through modeling and simulation(M&S) using the Discrete Event System Specification formalism (DEVS) due to its modular and hierarchical aspects, which improve the explainability of the models. In particular, the separation between the agent and the environment components involved in the traditional reinforcement learning (RL) algorithm, such as Q-Learning, is clearly formalized to enhance observability and envision the integration of AI components in the decision-making process. Our proposed DEVS model also improves the trust of decision makers by mitigating the risk of delegation to machines in decision-making processes. The main focus of this work is to provide the possibility of designing a Markovian system with a modeling and simulation formalism to optimize a decision-making process with greater explainability through simulation. Furthermore, the work involves an investigation based on financial process management, its specification as an MDP-based RL system, and its M&S with DEVS formalism.Books on Demand GmbH, Überseering 33, 22297 Hamburg 168 pp. Englisch. Seller Inventory # 9786206846697
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