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Alain Bensoussan

Researcher at University of Texas at Dallas

Publications -  435
Citations -  24109

Alain Bensoussan is an academic researcher from University of Texas at Dallas. The author has contributed to research in topics: Stochastic control & Optimal control. The author has an hindex of 55, co-authored 417 publications receiving 22704 citations. Previous affiliations of Alain Bensoussan include Northwestern University & EMLYON Business School.

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Some Results on Risk-Sensitive Control with Full Observation

TL;DR: In this paper, the Bellman equation of the risk sensitive control problem with full observation is considered, and it appears as an example of a quasi-linear parabolic equation in the whole space and fairly general growth assumptions with respect to the space variable x are permitted.
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Some results on risk-sensitive control with full observation

TL;DR: In this article, the authors considered the risk-sensitive control problem under general assumptions, in particular as far growth conditions are concerned, and considered the case of small variance of the noises and study the limit, which is related to robust control.
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Optimum inventory and product quality control with deterministic and stochastic deterioration--An application of distributed parameters control systems

TL;DR: In this article, the authors provide an analytic solution to both the deterministic and stochastic deterioration problems in inventory models with and without a deterministic deterioration rate, and the importance of such inventory models is to be found when the demand and value of stored products is also dependent on their quality.
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Mean-Field-Game Model for Botnet Defense in Cyber-Security

TL;DR: In this article, the authors model the response of computer owners to various offers of defence systems against a cyber-hacker as a stochastic game of a large number of interacting agents.
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On the optimal control of partially observed inventory systems

TL;DR: The existence of the optimal feedback policies are proved for two models where demand and inventory are partially observed and the optimality of the basestock policies are established, hence generalizing the corresponding classical models with full information.