Ivana Dusparić

Parallel Transfer Learning in Multi-Agent Systems: What, when and how to transfer?

2019

Multi-agent Reinforcement Learning (RL) is frequently used in large-scale autonomous systems to learn the behaviours that best suit the system's operating environment. Learning can take a significant amount of time during which an RL system's …

Iterative Reward Shaping using Human Feedback for Correcting Reward Misspecification

2023 · arXiv (Cornell University)

A well-defined reward function is crucial for successful training of an reinforcement learning (RL) agent. However, defining a suitable reward function is a notoriously challenging task, especially in complex, multi-objective environments. Developers often have to …

Multi-Objective Deep Reinforcement Learning Optimisation in Autonomous Systems

2024

Reinforcement Learning (RL) is used extensively in Autonomous Systems (AS) as it enables learning at runtime without the need for a model of the environment or predefined actions. However, most applications of RL in AS, …