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1647-2019 - IEEE Standard for the Functional Verification Language e / / Institute of Electrical and Electronics Engineers
1647-2019 - IEEE Standard for the Functional Verification Language e / / Institute of Electrical and Electronics Engineers
Pubbl/distr/stampa [Place of publication not identified] : , : IEEE, , 2019
Descrizione fisica 1 online resource (46 pages)
Disciplina 519.703
Soggetto topico Dynamic programming
ISBN 1-5044-5977-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910333852103321
[Place of publication not identified] : , : IEEE, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
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1647-2019 - IEEE Standard for the Functional Verification Language e / / Institute of Electrical and Electronics Engineers
1647-2019 - IEEE Standard for the Functional Verification Language e / / Institute of Electrical and Electronics Engineers
Pubbl/distr/stampa [Place of publication not identified] : , : IEEE, , 2019
Descrizione fisica 1 online resource (46 pages)
Disciplina 519.703
Soggetto topico Dynamic programming
ISBN 1-5044-5977-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996575391803316
[Place of publication not identified] : , : IEEE, , 2019
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning : Honolulu, HI, 1-5 April 2007
2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning : Honolulu, HI, 1-5 April 2007
Pubbl/distr/stampa [Place of publication not identified], : IEEE, 2007
Disciplina 519.7/03
Soggetto topico Dynamic programming
Machine learning
Operations Research
Civil & Environmental Engineering
Engineering & Applied Sciences
ISBN 1-5090-8720-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996201767103316
[Place of publication not identified], : IEEE, 2007
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning : Honolulu, HI, 1-5 April 2007
2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning : Honolulu, HI, 1-5 April 2007
Pubbl/distr/stampa [Place of publication not identified], : IEEE, 2007
Disciplina 519.7/03
Soggetto topico Dynamic programming
Machine learning
Operations Research
Civil & Environmental Engineering
Engineering & Applied Sciences
ISBN 9781509087204
1509087206
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910143037403321
[Place of publication not identified], : IEEE, 2007
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Adaptive dynamic programming for control : algorithms and stability / / Huaguang Zhang ... [et al.]
Adaptive dynamic programming for control : algorithms and stability / / Huaguang Zhang ... [et al.]
Autore Zhang Huaguang
Edizione [1st ed. 2013.]
Pubbl/distr/stampa New York, : Springer, 2013
Descrizione fisica 1 online resource (431 p.)
Disciplina 629.836
Collana Communications and control engineering
Soggetto topico Dynamic programming
Algorithms
ISBN 1-4471-4757-X
1-283-93343-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Optimal Stabilization Control for Discrete-time Systems -- Optimal Tracking Control for Discrete-time Systems -- Optimal Stabilization Control for Nonlinear Systems with Time Delays -- Optimal Tracking Control for Nonlinear Systems with Time-delays -- Optimal Feedback Control for Continuous-time Systems via ADP -- Several Special Optimal Feedback Control Designs Based on ADP -- Zero-sum Games for Discrete-time Systems Based on Model-free ADP -- Nonlinear Games for a Class of Continuous-time Systems Based on ADP -- Other Applications of ADP.
Record Nr. UNINA-9910437907603321
Zhang Huaguang  
New York, : Springer, 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Applied optimal control : optimization, estimation, and control / Arthur E. Bryson, Yu-Chi Ho
Applied optimal control : optimization, estimation, and control / Arthur E. Bryson, Yu-Chi Ho
Autore Bryson, Arthur E. (Arthur Earl)
Edizione [Rev. printing]
Pubbl/distr/stampa New York : Taylor & Francis, c1975
Descrizione fisica 481 p. : ill. ; 24 cm
Disciplina 629.8312
Altri autori (Persone) Ho, Yu-Chi, 1934-author
Soggetto topico Control theory
Mathematical optimization
Dynamic programming
ISBN 0891162283
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991001426839707536
Bryson, Arthur E. (Arthur Earl)  
New York : Taylor & Francis, c1975
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Approximate dynamic programming [[electronic resource] ] : solving the curses of dimensionality / / Warren B. Powell
Approximate dynamic programming [[electronic resource] ] : solving the curses of dimensionality / / Warren B. Powell
Autore Powell Warren B. <1955->
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, N.J., : J. Wiley & Sons, c2011
Descrizione fisica 1 online resource (658 p.)
Disciplina 519.7/03
519.703
Collana Wiley series in probability and statistics
Soggetto topico Dynamic programming
Programming (Mathematics)
ISBN 1-283-27370-5
9786613273703
1-118-02916-X
1-118-02917-8
1-118-02915-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Approximate Dynamic Programming; Contents; Preface to the Second Edition; Preface to the First Edition; Acknowledgments; 1 The Challenges of Dynamic Programming; 1.1 A Dynamic Programming Example: A Shortest Path Problem; 1.2 The Three Curses of Dimensionality; 1.3 Some Real Applications; 1.4 Problem Classes; 1.5 The Many Dialects of Dynamic Programming; 1.6 What Is New in This Book?; 1.7 Pedagogy; 1.8 Bibliographic Notes; 2 Some Illustrative Models; 2.1 Deterministic Problems; 2.2 Stochastic Problems; 2.3 Information Acquisition Problems; 2.4 A Simple Modeling Framework for Dynamic Programs
2.5 Bibliographic NotesProblems; 3 Introduction to Markov Decision Processes; 3.1 The Optimality Equations; 3.2 Finite Horizon Problems; 3.3 Infinite Horizon Problems; 3.4 Value Iteration; 3.5 Policy Iteration; 3.6 Hybrid Value-Policy Iteration; 3.7 Average Reward Dynamic Programming; 3.8 The Linear Programming Method for Dynamic Programs; 3.9 Monotone Policies*; 3.10 Why Does It Work?**; 3.11 Bibliographic Notes; Problems; 4 Introduction to Approximate Dynamic Programming; 4.1 The Three Curses of Dimensionality (Revisited); 4.2 The Basic Idea; 4.3 Q-Learning and SARSA
4.4 Real-Time Dynamic Programming4.5 Approximate Value Iteration; 4.6 The Post-Decision State Variable; 4.7 Low-Dimensional Representations of Value Functions; 4.8 So Just What Is Approximate Dynamic Programming?; 4.9 Experimental Issues; 4.10 But Does It Work?; 4.11 Bibliographic Notes; Problems; 5 Modeling Dynamic Programs; 5.1 Notational Style; 5.2 Modeling Time; 5.3 Modeling Resources; 5.4 The States of Our System; 5.5 Modeling Decisions; 5.6 The Exogenous Information Process; 5.7 The Transition Function; 5.8 The Objective Function; 5.9 A Measure-Theoretic View of Information**
5.10 Bibliographic NotesProblems; 6 Policies; 6.1 Myopic Policies; 6.2 Lookahead Policies; 6.3 Policy Function Approximations; 6.4 Value Function Approximations; 6.5 Hybrid Strategies; 6.6 Randomized Policies; 6.7 How to Choose a Policy?; 6.8 Bibliographic Notes; Problems; 7 Policy Search; 7.1 Background; 7.2 Gradient Search; 7.3 Direct Policy Search for Finite Alternatives; 7.4 The Knowledge Gradient Algorithm for Discrete Alternatives; 7.5 Simulation Optimization; 7.6 Why Does It Work?**; 7.7 Bibliographic Notes; Problems; 8 Approximating Value Functions; 8.1 Lookup Tables and Aggregation
8.2 Parametric Models8.3 Regression Variations; 8.4 Nonparametric Models; 8.5 Approximations and the Curse of Dimensionality; 8.6 Why Does It Work?**; 8.7 Bibliographic Notes; Problems; 9 Learning Value Function Approximations; 9.1 Sampling the Value of a Policy; 9.2 Stochastic Approximation Methods; 9.3 Recursive Least Squares for Linear Models; 9.4 Temporal Difference Learning with a Linear Model; 9.5 Bellman's Equation Using a Linear Model; 9.6 Analysis of TD(0), LSTD, and LSPE Using a Single State; 9.7 Gradient-Based Methods for Approximate Value Iteration*
9.8 Least Squares Temporal Differencing with Kernel Regression*
Record Nr. UNINA-9910139593803321
Powell Warren B. <1955->  
Hoboken, N.J., : J. Wiley & Sons, c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Approximate dynamic programming : solving the curses of dimensionality / / Warren B. Powell
Approximate dynamic programming : solving the curses of dimensionality / / Warren B. Powell
Autore Powell Warren B. <1955->
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, N.J., : J. Wiley & Sons, c2011
Descrizione fisica 1 online resource (658 p.)
Disciplina 519.7/03
Collana Wiley series in probability and statistics
Soggetto topico Dynamic programming
Programming (Mathematics)
ISBN 1-283-27370-5
9786613273703
1-118-02916-X
1-118-02917-8
1-118-02915-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Approximate Dynamic Programming; Contents; Preface to the Second Edition; Preface to the First Edition; Acknowledgments; 1 The Challenges of Dynamic Programming; 1.1 A Dynamic Programming Example: A Shortest Path Problem; 1.2 The Three Curses of Dimensionality; 1.3 Some Real Applications; 1.4 Problem Classes; 1.5 The Many Dialects of Dynamic Programming; 1.6 What Is New in This Book?; 1.7 Pedagogy; 1.8 Bibliographic Notes; 2 Some Illustrative Models; 2.1 Deterministic Problems; 2.2 Stochastic Problems; 2.3 Information Acquisition Problems; 2.4 A Simple Modeling Framework for Dynamic Programs
2.5 Bibliographic NotesProblems; 3 Introduction to Markov Decision Processes; 3.1 The Optimality Equations; 3.2 Finite Horizon Problems; 3.3 Infinite Horizon Problems; 3.4 Value Iteration; 3.5 Policy Iteration; 3.6 Hybrid Value-Policy Iteration; 3.7 Average Reward Dynamic Programming; 3.8 The Linear Programming Method for Dynamic Programs; 3.9 Monotone Policies*; 3.10 Why Does It Work?**; 3.11 Bibliographic Notes; Problems; 4 Introduction to Approximate Dynamic Programming; 4.1 The Three Curses of Dimensionality (Revisited); 4.2 The Basic Idea; 4.3 Q-Learning and SARSA
4.4 Real-Time Dynamic Programming4.5 Approximate Value Iteration; 4.6 The Post-Decision State Variable; 4.7 Low-Dimensional Representations of Value Functions; 4.8 So Just What Is Approximate Dynamic Programming?; 4.9 Experimental Issues; 4.10 But Does It Work?; 4.11 Bibliographic Notes; Problems; 5 Modeling Dynamic Programs; 5.1 Notational Style; 5.2 Modeling Time; 5.3 Modeling Resources; 5.4 The States of Our System; 5.5 Modeling Decisions; 5.6 The Exogenous Information Process; 5.7 The Transition Function; 5.8 The Objective Function; 5.9 A Measure-Theoretic View of Information**
5.10 Bibliographic NotesProblems; 6 Policies; 6.1 Myopic Policies; 6.2 Lookahead Policies; 6.3 Policy Function Approximations; 6.4 Value Function Approximations; 6.5 Hybrid Strategies; 6.6 Randomized Policies; 6.7 How to Choose a Policy?; 6.8 Bibliographic Notes; Problems; 7 Policy Search; 7.1 Background; 7.2 Gradient Search; 7.3 Direct Policy Search for Finite Alternatives; 7.4 The Knowledge Gradient Algorithm for Discrete Alternatives; 7.5 Simulation Optimization; 7.6 Why Does It Work?**; 7.7 Bibliographic Notes; Problems; 8 Approximating Value Functions; 8.1 Lookup Tables and Aggregation
8.2 Parametric Models8.3 Regression Variations; 8.4 Nonparametric Models; 8.5 Approximations and the Curse of Dimensionality; 8.6 Why Does It Work?**; 8.7 Bibliographic Notes; Problems; 9 Learning Value Function Approximations; 9.1 Sampling the Value of a Policy; 9.2 Stochastic Approximation Methods; 9.3 Recursive Least Squares for Linear Models; 9.4 Temporal Difference Learning with a Linear Model; 9.5 Bellman's Equation Using a Linear Model; 9.6 Analysis of TD(0), LSTD, and LSPE Using a Single State; 9.7 Gradient-Based Methods for Approximate Value Iteration*
9.8 Least Squares Temporal Differencing with Kernel Regression*
Record Nr. UNINA-9910822581503321
Powell Warren B. <1955->  
Hoboken, N.J., : J. Wiley & Sons, c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Decision and control in uncertain resource systems / Marc Mangel
Decision and control in uncertain resource systems / Marc Mangel
Autore Mangel, Marc
Pubbl/distr/stampa Orlando : Academic Press, c1985
Descrizione fisica xiii, 255 p. : ill. ; 24 cm
Disciplina 519.2
Collana Mathematics in science and engineering. A series of monographs and textbooks, 0076-5392 ; 172
Soggetto topico Control theory
Dynamic programming
Natural resources
Renewable natural resources
Stochastic processes
ISBN 0124687202
Classificazione AMS 93E
QA274.M35
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991000806559707536
Mangel, Marc  
Orlando : Academic Press, c1985
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Decision theory : an introduction to dynamic programming and sequential decisions / John Bather
Decision theory : an introduction to dynamic programming and sequential decisions / John Bather
Autore Bather, John
Pubbl/distr/stampa Chichester ; New York : Wiley, c2000
Descrizione fisica ix, 191 p. : ill. ; 23 cm.
Disciplina 519.542
Collana Wiley-Interscience series in systems and optimization
Soggetto topico Decision making
Dynamic programming
ISBN 0471976490 (pbk. : alk. paper)
Classificazione AMS 62C
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991003676249707536
Bather, John  
Chichester ; New York : Wiley, c2000
Materiale a stampa
Lo trovi qui: Univ. del Salento
Opac: Controlla la disponibilità qui