collaborators

6 papers

cs.LG2025

Spiders Based on Anxiety: How Reinforcement Learning Can Deliver Desired User Experience in Virtual Reality Personalized Arachnophobia Treatment

Athar Mahmoudi-Nejad, Matthew Guzdial, Pierre Boulanger

The need to generate a spider to provoke a desired anxiety response arises in the context of personalized virtual reality exposure therapy (VRET), a treatment approach for arachnop…

cs.AI2025

A Systematic Approach to Design Real-World Human-in-the-Loop Deep Reinforcement Learning: Salient Features, Challenges and Trade-offs

Jalal Arabneydi, Saiful Islam, Srijita Das +7

With the growing popularity of deep reinforcement learning (DRL), human-in-the-loop (HITL) approach has the potential to revolutionize the way we approach decision-making problems…

cs.LG2025

Personalizing Exposure Therapy via Reinforcement Learning

Athar Mahmoudi-Nejad, Matthew Guzdial, Pierre Boulanger

Personalized therapy, in which a therapeutic practice is adapted to an individual patient, can lead to improved health outcomes. Typically, this is accomplished by relying on a the…

cs.HC2024

Label-Free Subjective Player Experience Modelling via Let's Play Videos

Dave Goel, Athar Mahmoudi-Nejad, Matthew Guzdial

Player Experience Modelling (PEM) is the study of AI techniques applied to modelling a player's experience within a video game. PEM development can be labour-intensive, requiring e…

cs.HC2024

Mechanic Maker: Accessible Game Development Via Symbolic Learning Program Synthesis

Megan Sumner, Vardan Saini, Matthew Guzdial

Game development is a highly technical practice that traditionally requires programming skills. This serves as a barrier to entry for would-be developers or those hoping to use gam…

cs.HC2024

Evaluating the Effects of AI Directors for Quest Selection

Kristen K. Yu, Matthew Guzdial, Nathan Sturtevant

Modern commercial games are designed for mass appeal, not for individual players, but there is a unique opportunity in video games to better fit the individual through adapting gam…