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Variable Stiffness Control for Sequential Contact Tasks
Reasoning about MDPs Abstractly: Bayesian Policy Search with Uncertain Prior Knowledge
Dyadic Physical Activity Planning with a Virtual Coach: Using Reinforcement Learning to Select Persuasive Strategies
Regret Analysis of Learning-Based Linear Quadratic Gaussian Control with Additive Exploration
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
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?
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?
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 Decision Trees produced by Generative Adversarial Imitation Learning to give insight into black box Reinforcement Learning models
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
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