A reference-decoupled reformulation makes direct data-driven LQT equivalent to certainty-equivalence solutions and supports convergent offline and online DeePO algorithms.
Consensus problems in networks of agents with switching topology and time-delays
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ARGFree is the first gradient-free method for aggregative cooperative optimization, converging in expectation to an approximate solution via randomized finite differences and tracking, with a momentum-enhanced variant for high dimensions.
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Direct Data-Driven Linear Quadratic Tracking via Policy Optimization
A reference-decoupled reformulation makes direct data-driven LQT equivalent to certainty-equivalence solutions and supports convergent offline and online DeePO algorithms.
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Model-Free Aggregative Cooperative Optimization via Randomized Gradient-Free Minimization and Exploration Momentum
ARGFree is the first gradient-free method for aggregative cooperative optimization, converging in expectation to an approximate solution via randomized finite differences and tracking, with a momentum-enhanced variant for high dimensions.