Results 11 to 20 of about 14,953 (260)
Functional Approximations and Dynamic Programming [PDF]
Mathematical Tables and Other Aids to Computation, 1959 Abstract : This paper indicates some ways in which the theory of approximation can be used to increase the range of present day computers. Although the primary interest is in applying these techniques to the functional equations occurring in the theory of dynamic programming.
Bellman, Richard, Dreyfus, Stuart
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A review of approximate dynamic programming applications within military operations research
Operations Research Perspectives, 2021 Sequences of decisions that occur under uncertainty arise in a variety of settings, including transportation, communication networks, finance, defence, etc.
M. Rempel, J. Cai
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Output‐feedback stochastic model predictive control of chance‐constrained nonlinear systems
IET Control Theory & Applications, 2023 This study covers the output‐feedback model predictive control (MPC) of nonlinear systems subjected to stochastic disturbances and state chance constraints. The stochastic optimal control problem is solved in a stochastic dynamic programming fashion, and
Jingyu Zhang, Toshiyuki Ohtsuka
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Volume-weighted Bellman error method for adaptive meshing in approximate dynamic programming
Revista Iberoamericana de Automática e Informática Industrial RIAI, 2021 Optimal control and reinforcement learning have an associate “value function” which must be suitably approximated. Value function approximation problems usually have different precision requirements in different regions of the state space.
Leopoldo Armesto, Antonio Sala
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Link Scheduling for Wireless Mesh Networks Considering Gateway Feature [PDF]
EAI Endorsed Transactions on Internet of Things, 2020 Based on different objectives, a variety of mathematical models for the wireless mesh network (WMNs) exist. Among them, the link scheduling model for WMNs aims at finding a data transmission schedule based on network links so that some ...
Chun-Cheng Lin +2 more
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Approximate Dynamic Programming Methodology for Data-based Optimal Controllers
Revista Iberoamericana de Automática e Informática Industrial RIAI, 2019 In this article, we present a methodology for learning data-based approximately optimal controllers, within the context of learning and approximate dynamic programming.
Henry Díaz +2 more
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Social Sciences and Humanities Open, 2022 Discrete-choice life cycle models of labor supply can be used to estimate how social security reforms influence employment rate. In a life cycle model, optimal employment choices during the life course of an individual must be solved.
Antti J. Tanskanen
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Tuning approximate dynamic programming policies for ambulance redeployment via direct search
Stochastic Systems, 2014 In this paper we consider approximate dynamic programming methods for ambulance redeployment. We first demonstrate through simple examples how typical value function fitting techniques, such as approximate policy iteration and linear programming, may not
Matthew S. Maxwell +2 more
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Journal of Advanced Transportation, 2022 The bicycle, an active transportation mode, has received increasing attention as an alternative in urban environments worldwide. However, effectively managing the stock levels of rental bicycles at each station is challenging as demand levels vary with ...
Young-Hyun Seo +4 more
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A reinforcement learning approach to the stochastic cutting stock problem
EURO Journal on Computational Optimization, 2022 We propose a formulation of the stochastic cutting stock problem as a discounted infinite-horizon Markov decision process. At each decision epoch, given current inventory of items, an agent chooses in which patterns to cut objects in stock in ...
Anselmo R. Pitombeira-Neto +1 more
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