Forward-Backward Sweep Method for the System of HJB-FP Equations in Memory-Limited Partially Observable Stochastic Control [PDF]
Memory-limited partially observable stochastic control (ML-POSC) is the stochastic optimal control problem under incomplete information and memory limitation.
Takehiro Tottori, Tetsuya J. Kobayashi
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Memory-Limited Partially Observable Stochastic Control and Its Mean-Field Control Approach [PDF]
Control problems with incomplete information and memory limitation appear in many practical situations. Although partially observable stochastic control (POSC) is a conventional theoretical framework that considers the optimal control problem with ...
Takehiro Tottori, Tetsuya J. Kobayashi
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Decentralized Stochastic Control with Finite-Dimensional Memories: A Memory Limitation Approach [PDF]
Decentralized stochastic control (DSC) is a stochastic optimal control problem consisting of multiple controllers. DSC assumes that each controller is unable to accurately observe the target system and the other controllers.
Takehiro Tottori, Tetsuya J. Kobayashi
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Decision to choose optimal trading position in future contracts of consumer goods with stochastic control and based on storage theory and convenience yield [PDF]
Purpose: The main theory governing the valuation of futures contracts is the Storage Theory, in which the concept of Convenience Yield is the most important factor involved in contract pricing.
Mehdi Khajezadeh Dezfoli +3 more
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Control problems are always challenging since they arise from the real-world systems where stochasticity and randomness are of ubiquitous presence. This naturally and urgently calls for developing efficient neural control policies for stabilizing not only the deterministic equations but the stochastic systems as well.
Jingdong Zhang 0001 +2 more
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Decentralized stochastic control [PDF]
Decentralized stochastic control refers to the multi-stage optimization of a dynamical system by multiple controllers that have access to different information. Decentralization of information gives rise to new conceptual challenges that require new solution approaches.
Aditya Mahajan, Mehnaz Mannan
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Active Inference for Stochastic Control [PDF]
12 pages, 5 figures, Accepted presentation at IWAI-2021 (ECML-PKDD)
Aswin Paul +3 more
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Control mechanisms for stochastic biochemical systems via computation of reachable sets [PDF]
Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear.
Eszter Lakatos, Michael P. H. Stumpf
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A Semi-Markov Dynamic Capital Injection Problem for Distressed Banks
Our study investigates the optimal dividend strategy for a bank, taking into account the potential for government capital injections. We explore different types of government interventions, such as liberal, transparent, or uncertain strategies, and ...
Luca Di Persio +2 more
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Optimal lock-down intensity: A stochastic pandemic control approach of path integral
The aim of this article is to determine the optimal intensity of lock-down measures and vaccination rates to control the spread of coronavirus disease 2019. The study uses a stochastic susceptible-infected-recovered (SIR) model with infection dynamics. A
Pramanik Paramahansa
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