Eivind Bøhn | DeepAI

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∙ 06/06/2022

Port-Hamiltonian Neural Networks with State Dependent Ports

Hybrid machine learning based on Hamiltonian formulations has recently b...

0 Sølve Eidnes, et al. ∙

∙ 11/07/2021

Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experiments

Attitude control of fixed-wing unmanned aerial vehicles (UAVs)is a diffi...

9 Eivind Bøhn, et al. ∙

∙ 11/07/2021

Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning

Model predictive control (MPC) is increasingly being considered for cont...

0 Eivind Bøhn, et al. ∙

∙ 02/22/2021

Reinforcement Learning of the Prediction Horizon in Model Predictive Control

Model predictive control (MPC) is a powerful trajectory optimization con...

0 Eivind Bøhn, et al. ∙

∙ 11/26/2020

Optimization of the Model Predictive Control Update Interval Using Reinforcement Learning

In control applications there is often a compromise that needs to be mad...

0 Eivind Bøhn, et al. ∙

∙ 11/21/2019

Accelerating Reinforcement Learning with Suboptimal Guidance

Reinforcement Learning in domains with sparse rewards is a difficult pro...

0 Eivind Bøhn, et al. ∙

∙ 11/13/2019

Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimization

Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are f...

0 Eivind Bøhn, et al. ∙

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