109 citations · 277 across the 50 of their papers we have counts for
54 papers
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…
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…
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…
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…
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…
Stress Detection from Photoplethysmography in a Virtual Reality Environment
Athar Mahmoudi-Nejad, Pierre Boulanger, Matthew Guzdial
Personalized virtual reality exposure therapy is a therapeutic practice that can adapt to an individual patient, leading to better health outcomes. Measuring a patient's mental sta…
A Framework for Predicting the Impact of Game Balance Changes through Meta Discovery
Akash Saravanan, Matthew Guzdial
A metagame is a collection of knowledge that goes beyond the rules of a game. In competitive, team-based games like Pokémon or League of Legends, it refers to the set of current do…
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…
Human-AI Collaboration in Real-World Complex Environment with Reinforcement Learning
Md Saiful Islam, Srijita Das, Sai Krishna Gottipati +6
Recent advances in reinforcement learning (RL) and Human-in-the-Loop (HitL) learning have made human-AI collaboration easier for humans to team with AI agents. Leveraging human exp…
Tree-Based Reconstructive Partitioning: A Novel Low-Data Level Generation Approach
Emily Halina, Matthew Guzdial
Procedural Content Generation (PCG) is the algorithmic generation of content, often applied to games. PCG and PCG via Machine Learning (PCGML) have appeared in published games. How…
Game Level Blending using a Learned Level Representation
Venkata Sai Revanth Atmakuri, Seth Cooper, Matthew Guzdial
Game level blending via machine learning, the process of combining features of game levels to create unique and novel game levels using Procedural Content Generation via Machine Le…
Joint Level Generation and Translation Using Gameplay Videos
Negar Mirgati, Matthew Guzdial
Procedural Content Generation via Machine Learning (PCGML) faces a significant hurdle that sets it apart from other fields, such as image or text generation, which is limited annot…
Transfer Learning for Underrepresented Music Generation
Anahita Doosti, Matthew Guzdial
This paper investigates a combinational creativity approach to transfer learning to improve the performance of deep neural network-based models for music generation on out-of-distr…
Procedural Content Generation via Knowledge Transformation (PCG-KT)
Anurag Sarkar, Matthew Guzdial, Sam Snodgrass +3
We introduce the concept of Procedural Content Generation via Knowledge Transformation (PCG-KT), a new lens and framework for characterizing PCG methods and approaches in which con…
Generating Real-Time Strategy Game Units Using Search-Based Procedural Content Generation and Monte Carlo Tree Search
Kynan Sorochan, Matthew Guzdial
Real-Time Strategy (RTS) game unit generation is an unexplored area of Procedural Content Generation (PCG) research, which leaves the question of how to automatically generate inte…
Improving Deep Localized Level Analysis: How Game Logs Can Help
Natalie Bombardieri, Matthew Guzdial
Player modelling is the field of study associated with understanding players. One pursuit in this field is affect prediction: the ability to predict how a game will make a player f…
Diversity-based Deep Reinforcement Learning Towards Multidimensional Difficulty for Fighting Game AI
Emily Halina, Matthew Guzdial
In fighting games, individual players of the same skill level often exhibit distinct strategies from one another through their gameplay. Despite this, the majority of AI agents for…
Clustering-based Tile Embedding (CTE): A General Representation for Level Design with Skewed Tile Distributions
Mrunal Jadhav, Matthew Guzdial
There has been significant research interest in Procedural Level Generation via Machine Learning (PLGML), applying ML techniques to automated level generation. One recent trend is…
Responsibility: An Example-based Explainable AI approach via Training Process Inspection
Faraz Khadivpour, Arghasree Banerjee, Matthew Guzdial
Explainable Artificial Intelligence (XAI) methods are intended to help human users better understand the decision making of an AI agent. However, many modern XAI approaches are uni…
SketchBetween: Video-to-Video Synthesis for Sprite Animation via Sketches
Dagmar Lukka Loftsdóttir, Matthew Guzdial
2D animation is a common factor in game development, used for characters, effects and background art. It involves work that takes both skill and time, but parts of which are repeti…
Threshold Designer Adaptation: Improved Adaptation for Designers in Co-creative Systems
Emily Halina, Matthew Guzdial
To best assist human designers with different styles, Machine Learning (ML) systems need to be able to adapt to them. However, there has been relatively little prior work on how an…
Pixel VQ-VAEs for Improved Pixel Art Representation
Akash Saravanan, Matthew Guzdial
Machine learning has had a great deal of success in image processing. However, the focus of this work has largely been on realistic images, ignoring more niche art styles such as p…
The Definition-Context-Purpose Paradigm and Other Insights from Industry Professionals About the Definition of a Quest
Kristen K. Yu, Matthew Guzdial, Nathan R. Sturtevant
Among academic communities there is no single agreed upon definition of a quest. The industry perspective on this topic is also largely unknown. Thus, thee purpose of this paper is…
The Impact of Visualizing Design Gradients for Human Designers
Matthew Guzdial, Nathan Sturtevant, Carolyn Yang
Mixed-initiative Procedural Content Generation (PCG) refers to tools or systems in which a human designer works with an algorithm to produce game content. This area of research rem…