Reinforcement learning (RL) has been successfully applied to motion control, without
requiring accurate models and selection of control parameters. In this paper, we propose a …

In the paper, a new evolutionary technique called Linear Matrix Genetic Programming
(LMGP) is proposed. It is a matrix extension of Linear Genetic Programming and its …

Learning-based adaptive control methods hold the potential to empower autonomous
agents in mitigating the impact of process variations with minimal human intervention …

In this paper we investigate a direct adaptive learning-based tuning strategy for the control of
an underwater vehicle under unknown disturbances. This process can be seen as a double …

Abstract Underwater Unmanned Vehicles (UUVs) have to constantly compensate for the
external disturbing forces acting on their body. Adaptive Control theory is commonly used …

Deep Reinforcement Learning (DRL) methods are dominating the field of adaptive control
where they are used to adapt the controller response to disturbances. Nevertheless, the …

The paper addresses the problem of modeling complex nonlinear objects such as
underwater vehicles. To solve this problem, a new evolutionary technique called Linear …