Discrete Event Modeling and Simulation of Markov Decision Process.: Application to the Leverage Effects in Financial Asset Optimization Processes. - Couverture souple

BARBIERI, Emanuele; CAPOCCHI, Laurent; SANTUCCI, Jean-Fran�ois

9786206846697: Discrete Event Modeling and Simulation of Markov Decision Process.: Application to the Leverage Effects in Financial Asset Optimization Processes.

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ISBN 10 : 6206846695 ISBN 13 : 9786206846697

Editeur : LAP LAMBERT Academic Publishing, 2023

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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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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2023
Langue: anglais
ISBN 10: 6206846695
ISBN 13: 9786206846697
Reliure: Broch�
Nombre de pages: 168
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Discrete Event Modeling and Simulation of Markov Decision Process.

BARBIERI, Emanuele|CAPOCCHI, Laurent|SANTUCCI, Jean-Fran�ois

Edit� par LAP Lambert Academic Publishing, 2023

ISBN 10 : 6206846695 ISBN 13 : 9786206846697

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Etat : 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. N� de r�f. du vendeur 1294647999

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Discrete Event Modeling and Simulation of Markov Decision Process.

Emanuele Barbieri

Edit� par LAP LAMBERT Academic Publishing Nov 2023, 2023

ISBN 10 : 6206846695 ISBN 13 : 9786206846697

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Taschenbuch. Etat : 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. N� de r�f. du vendeur 9786206846697

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Discrete Event Modeling and Simulation of Markov Decision Process. : Application to the Leverage Effects in Financial Asset Optimization Processes.

Emanuele Barbieri

Edit� par LAP LAMBERT Academic Publishing, 2023

ISBN 10 : 6206846695 ISBN 13 : 9786206846697

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Taschenbuch. Etat : 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. N� de r�f. du vendeur 9786206846697

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Discrete Event Modeling and Simulation of Markov Decision Process.

Emanuele Barbieri

Edit� par LAP LAMBERT Academic Publishing Nov 2023, 2023

ISBN 10 : 6206846695 ISBN 13 : 9786206846697

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Taschenbuch. Etat : 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, �berseering 33, 22297 Hamburg 168 pp. Englisch. N� de r�f. du vendeur 9786206846697

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