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Resumen de: EP4672084A1

The present invention relates to a computer-implemented method of training a pursuer neural network agent. The method comprising: providing an evader neural network agent trained to update iteratively a plurality of dynamic parameters of an evader, a pursuer neural network agent initialised to update iteratively a plurality of approximators for a pursuer, and an ordinary differential equation solver configured to update a plurality of dynamic parameters of the pursuer based on the updated approximators; sampling initial dynamic parameters from a set of initial dynamic parameters of the evader; running a simulation involving the pursuer neural network agent pursuing the evader neural network agent based on the sampled initial dynamic parameters; computing a loss based on the dynamic parameters of the pursuer from the ordinary differential equation solver and the dynamic parameters of the evader from the evader neural network agent; and optimising weights of the pursuer neural network agent based on the computed loss.