4 papers
A Model-Driven Approach for Developing Families of Reinforcement Learning Environments
Xiaoran Liu, Istvan David
Virtual training environments are software-intensive systems in which reinforcement learning (RL) agents learn, adapt, and demonstrate meaningful behavior. Virtual training environ…
Trust the AI, Doubt Yourself: The Effect of Urgency on Self-Confidence in Human-AI Interaction
Baran Shajari, Xiaoran Liu, Kyanna Dagenais +1
Studies show that interactions with an AI system fosters trust in human users towards AI. An often overlooked element of such interaction dynamics is the (sense of) urgency when th…
A Reference Architecture of Reinforcement Learning Frameworks
Xiaoran Liu, Istvan David
The surge in reinforcement learning (RL) applications gave rise to diverse supporting technology, such as RL frameworks. However, the architectural patterns of these frameworks are…
Complex Model Transformations by Reinforcement Learning with Uncertain Human Guidance
Kyanna Dagenais, Istvan David
Model-driven engineering problems often require complex model transformations (MTs), i.e., MTs that are chained in extensive sequences. Pertinent examples of such problems include…