Abdullah Tokmak
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View article: Towards safe control parameter tuning in distributed multi-agent systems
Towards safe control parameter tuning in distributed multi-agent systems Open
Many safety-critical real-world problems, such as autonomous driving and collaborative robots, are of a distributed multi-agent nature. To optimize the performance of these systems while ensuring safety, we can cast them as distributed opt…
View article: Safe exploration in reproducing kernel Hilbert spaces
Safe exploration in reproducing kernel Hilbert spaces Open
Popular safe Bayesian optimization (BO) algorithms learn control policies for safety-critical systems in unknown environments. However, most algorithms make a smoothness assumption, which is encoded by a known bounded norm in a reproducing…
View article: PACSBO: Probably approximately correct safe Bayesian optimization
PACSBO: Probably approximately correct safe Bayesian optimization Open
Safe Bayesian optimization (BO) algorithms promise to find optimal control policies without knowing the system dynamics while at the same time guaranteeing safety with high probability. In exchange for those guarantees, popular algorithms …
View article: Automatic nonlinear MPC approximation with closed-loop guarantees
Automatic nonlinear MPC approximation with closed-loop guarantees Open
Safety guarantees are vital in many control applications, such as robotics. Model predictive control (MPC) provides a constructive framework for controlling safety-critical systems, but is limited by its computational complexity. We addres…