Adaptive Deep Learning for High-Dimensional Hamilton--Jacobi--Bellman Equations
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Publication:4997364
DOI10.1137/19M1288802zbMath1467.49028arXiv1907.05317OpenAlexW3150654747MaRDI QIDQ4997364
Tenavi Nakamura-Zimmerer, Qi Gong, Wei Kang
Publication date: 29 June 2021
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1907.05317
optimizationoptimal feedback controlneural networksHamilton-Jacobi-Bellman equationsnonlinear dynamical systemsdeep learning
Nonlinear programming (90C30) Learning and adaptive systems in artificial intelligence (68T05) Dynamic programming in optimal control and differential games (49L20) Optimal feedback synthesis (49N35) Control/observation systems governed by partial differential equations (93C20) Control/observation systems governed by ordinary differential equations (93C15) Optimality conditions for problems involving ordinary differential equations (49K15)
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Uses Software
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