2 papers
cs.LG2026
Adapting the Behavior of Reinforcement Learning Agents to Changing Action Spaces and Reward Functions
Raul de la Rosa, Ivana Dusparic, Nicolas Cardozo
Reinforcement Learning (RL) agents often struggle in real-world applications where environmental conditions are non-stationary, particularly when reward functions shift or the avai…
cs.AI2024
Multi-Objective Deep Reinforcement Learning for Optimisation in Autonomous Systems
Juan C. Rosero, Ivana Dusparic, Nicolás Cardozo
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.…