no code implementations • 7 Sep 2023 • Oliver Gates, Matthew Newton, Konstantinos Gatsis
This paper addresses the problem of finding overapproximations of forward reachable sets for discrete-time uncertain multi-agent systems with distributed NNC architectures.
no code implementations • 12 Jul 2023 • Matthew Newton, Antonis Papachristodoulou
However, one prominent issue with these methods is that they use existing neural network architectures tailored for traditional machine learning tasks.
no code implementations • 8 Apr 2022 • Matthew Newton, Antonis Papachristodoulou
These higher order Lyapunov functions are used in conjunction with higher order multipliers on the inequality and equality constraints that bound the neural network input-output properties.
no code implementations • 4 Feb 2022 • Matthew Newton, Antonis Papachristodoulou
Depending on the complexity of these bounds, the computational time of the optimisation problem varies, with longer solve times often leading to tighter bounds.
