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

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

Sinopsis

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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BARBIERI, Emanuele|CAPOCCHI, Laurent|SANTUCCI, Jean-François
Publicado por LAP Lambert Academic Publishing, 2023
ISBN 10: 6206846695 ISBN 13: 9786206846697
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Condición: 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. Nº de ref. del artículo: 1294647999

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Emanuele Barbieri
ISBN 10: 6206846695 ISBN 13: 9786206846697
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786206846697

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Emanuele Barbieri
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695 ISBN 13: 9786206846697
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786206846697

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BARBIERI, Emanuele; CAPOCCHI, Laurent; SANTUCCI, Jean-François
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695 ISBN 13: 9786206846697
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BARBIERI, Emanuele; CAPOCCHI, Laurent; SANTUCCI, Jean-François
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BARBIERI, Emanuele; CAPOCCHI, Laurent; SANTUCCI, Jean-François
Publicado por LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206846695 ISBN 13: 9786206846697
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Emanuele Barbieri
ISBN 10: 6206846695 ISBN 13: 9786206846697
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786206846697

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