Autonomous greenhouse climate control with Q-learning using ENMPC as a function approximator

Safe & Intelligent Control: Fault-tolerant Flight Control with Distributional and Hybrid Reinforcement Learning using DSAC and IDHP

Deep Reinforcement Learning for Aircraft Landing: A study on the use of Deep Reinforcement Learning techniques for automatic control of aircraft landing

A Method for Embodied Co-Learning in Interdependent Human-Robot Teams

Graph convolution reinforcement learning for active wake control in windfarms: Application of a multi-agent reinforcement learning algorithm

Effects of action space discretization and DQN extensions on algorithm robustness and efficiency: How do the discretization of the action space and various extensions to the well-known DQN algorithm influence training and the robustness of final policies under various testing conditions?

Evaluating Robustness of Deep Reinforcement Learning for Autonomous Driving: How does entropy maximization affect the training and robustness of final policies under various testing conditions?

Modelling Agents with Variational Autoencoders in Multi-Agent Sequential Decision Making

Distributional Reinforcement Learning for Flight Control: A risk-sensitive approach to aircraft attitude control using Distributional RL

Deep Reinforcement Learning for the Automatic Six-Degree-of-Freedom Docking Maneuver of Space Vehicles

Learning-based path planning for automatic guided vehicles in container terminals: A case study at TBA Group

Learning the Problem Representation for Improving Negotiation Strategies

Using Explainable Artificial Intelligence to Improve Transparency of Reinforcement Learning for Online Adaptive Flight Control: Breaking Open the Black Box

Using Decision Trees produced by Generative Adversarial Imitation Learning to give insight into black box Reinforcement Learning models

Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems

MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response

Reinforcement learning with domain-­specific relational inductive biases: Using Graph Neural Networks and domain knowledge

Practical implementation of reinforcement learning algorithms for giving personalised speed advice to cyclists approaching intersections using function approximation and Dyna

Optimal Control Strategies for Seasonal Thermal Energy Storage Systems with Market Interaction

A Looseness Detection Method for Railway Catenary Fasteners based on Reinforcement Learning Refined Localization