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作者：Cayci, Semih; Satpathi, Siddhartha; He, Niao; Srikant, R.
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; RWTH Aachen University; University of Illinois System; University of Illinois Urbana-Champaign; Mayo Clinic; Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Illinois System; University of Illinois Urbana-Champaign
摘要：In this article, we study the dynamics of temporal-difference (TD) learning with neural network-based value function approximation over a general state space, namely, neural TD learning. We consider two practically used algorithms, projection-free and max-norm regularized neural TD learning, and establish the first convergence bounds for these algorithms. An interesting observation from our results is that max-norm regularization can dramatically improve the performance of TD learning algorith...
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作者：Schuurmans, Mathijs; Patrinos, Panagiotis
作者单位：KU Leuven
摘要：In this article, we present a data-driven learning model predictive control (MPC) scheme for chance-constrained Markov jump systems with unknown switching probabilities. Using samples of the underlying Markov chain, ambiguity sets of transition probabilities are estimated, which include the true conditional probability distributions with high probability. These sets are updated online and used to formulate a time-varying, risk-averse optimal control problem. We prove recursive feasibility of t...
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作者：Vinod, Abraham P.; Israel, Arie; Topcu, Ufuk
作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
摘要：We study the problem of data-driven, constrained control of unknown nonlinear dynamics from a single ongoing and finite-horizon trajectory. We consider a one-step optimal control problem with a smooth, black-box objective, typically a composition of a known cost function and the unknown dynamics. We investigate an on-the-fly control paradigm, i.e., at each time step, the evolution of the dynamics and the first-order information of the cost are provided only for the executed control action. We ...
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作者：Alanwar, Amr; Koch, Anne; Allgoewer, Frank; Johansson, Karl Henrik
作者单位：Royal Institute of Technology; Constructor University; University of Stuttgart; Royal Institute of Technology
摘要：We consider the problem of computing reachable sets directly from noisy data without a given system model. Several reachability algorithms are presented for different types of systems generating the data. First, an algorithm for computing over-approximated reachable sets based on matrix zonotopes is proposed for linear systems. Constrained matrix zonotopes are introduced to provide less conservative reachable sets at the cost of increased computational expenses and utilized to incorporate prio...
