Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimization. - Eivind Bøhn; Erlend M. Coates; Signe Moe; Tor Arne Johansen (CoRR, 2019)

Accelerating Reinforcement Learning with Suboptimal Guidance. - Eivind Bøhn; Signe Moe; Tor Arne Johansen (CoRR, 2019)

Optimization of the Model Predictive Control Update Interval Using Reinforcement Learning. - Eivind Bøhn; Sebastien Gros; Signe Moe; Tor Arne Johansen (CoRR, 2020)

On the Effects of Properties of the Minibatch in Reinforcement Learning. - Eivind Bøhn; Signe Moe; Tor Arne Johansen (INTAP, 2021)

Reinforcement Learning of the Prediction Horizon in Model Predictive Control. - Eivind Bøhn; Sebastien Gros; Signe Moe; Tor Arne Johansen (CoRR, 2021)

Port-Hamiltonian Neural Networks with State Dependent Ports. - Sølve Eidnes; Alexander J. Stasik; Camilla Sterud; Eivind Bøhn; Signe Riemer-Sørensen (CoRR, 2022)

Optimization of the model predictive control meta-parameters through reinforcement learning. - Eivind Bøhn; Sebastien Gros; Signe Moe; Tor Arne Johansen (Eng. Appl. Artif. Intell., 2023)

Recency-Weighted Temporally-Segmented Ensemble for Time-Series Modeling. - Pål V. Johnsen; Eivind Bøhn; Sølve Eidnes; Filippo Remonato; Signe Riemer-Sørensen (CoRR, 2024)

Machine learning in wastewater treatment: insights from modelling a pilot denitrification reactor. - Eivind Bøhn; Sølve Eidnes; Kjell Rune Jonassen (CoRR, 2024)

Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field Experiments. - Eivind Bøhn; Erlend M. Coates; Dirk Reinhardt; Tor Arne Johansen (IEEE Trans. Neural Networks Learn. Syst., 2024)