Graphics, Artificial Intelligence, Design, and Games Lab

We explore difficult problems in the representation, visibility, and decision-making of digital agents and humans. We create and innovate in human behaviour & movement modelling, human-centred artificial intelligence, game design, game AI, architectural optimization, augmented intelligence in complex design, assistive technologies, rehabilitative technologies, and more.

Complex Modern Agent Behaviours

Our group investigates techniques to diversify and modernize agent behaviours. Here is a screenshot from a simplified transit scenario where agents use event-driven and parametric behaviour trees in conjunction with probabilistic visual attention fields to model egocentric distractions like the use and impact of cell phones on crowd movement in modern urban environments.

High Fidelity Physical Crowds

The future of synthetic crowds for simulation, animation, safety-critical analysis, and design is ultra-high fidelity physically enabled crowds. Our group explores and developed new techniques in Reinforcement Learning, Multi-agent Reinforcement Learning, Deep Learning, Steering, Biomechanics, and Physical Character Control to support the next generation of crowds models and applications. These approaches support the modelling and animation of more diverse and representative crowds with a long-term goal of modelling disabilities, mobility devices, and cognition in synthetic crowds.

Human-Augmented Intelligence in Computer Aided Design

We improve design pipelines and strengthen outcomes and deliverables by augmenting designer skills with machine learning, artificial intelligence, and optimization via static and dynamic analysis. Our augmented pipelines produce environments that are human-aware and predictive to a broad range of scenarios.

Game Analysis, Optimization, and Adaptive Procedural Generation

Building more engaging games by understanding how players move and engage in the environment. Analyze and model the underlying difficulty to produce target level difficulties through optimization. Use these levels to procedurally augment player experience or provide options for player controlled experiences

Gamifying Rehabilitation

We develop game platforms based on high-fidelity clinical tracking and measurement tools. Using these platforms we engage in participatory design and development of visual metaphors and game mechanics for reaching rehabilitation goals. We drive characters and visualizations using computational geometry to capture clinical motor speech targets. This approach augments clinical practice to improve attrition rates in a variety of rehabilitation and therapy settings.

Augmenting Design Communication with Virtual Reality

Often complex designs are difficult to engage with. We explore and build interactive technologies using augmented and virtual reality to facilitate and streamline stakeholder and collaborator communication. Our platforms have highlighted and verified design flaws and errors while improving the accuracy of the perception of design choices.

Recent News

Graduate Awards for GAIDG Lab Members

Two GAIDG Lab Master's students have won the University of Victoria Graduate Award for their exceptional performance in the last two terms (high academic standing). GIADG Lab alumnus and affiliate...

Student wins Valerie Kuehne Undergraduate Research Award (VKURA) SU2022

Undergraduate student Liam Shatzel was awarded the Valerie Kuehne Undergraduate Research Award (VKURA)  for summer 2022 to work on complex agent representations in crowd simulation in the  GAIDG...

Paper accepted at Computers & Graphics Journal

Our short paper published at Motion, Interaction and Games 2021 was selected for extension in the Computers & Graphics journal. In collaboration with GAIDG Lab external collaborators, York...

Paper accepted at IEEE Transactions on Visualization and Computer Graphics Journal

In collaboration with GAIDG Lab external collaborators, York University's Prof. Petros Faloutsos, Université de Montréal and Mila member Prof. Glen Berseth, and Rutgers University's Prof. Mubbasir...

Paper Accepted at the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games

In collaboration with GAIDG Lab external collaborators, York University PI Petros Faloutsos, PhD Student Melissa Kremer, and Master’s student Peter Caruana, and Rutgers University PI Mubbasir...

Paper Accepted at the International Symposium on Visual Computing (ISVC) 2021

GAIDG Lab member, recent graduate, and incoming Masters student (January 2021) has work accepted as a full conference paper on using Convolutional Neural Networks to identify Solfege hand signs in...

Student wins Jamie Cassels Undergraduate Research Award (JCURA) 2021-2022

Undergraduate student Colin Johnson was awarded the Jamie Cassels Undergraduate Research Award (JCURA) 2021-2022 to work on vision and decision-making in navigation and signage accessibility with...

Alumnus Awarded W.E. Cowie Innovation Award for work with GAIDG Lab

Recent alumnus, Yiping Wang, has been selected for the W.E. Cowie Innovation award for work on Unsupervised Environment Design to facilitate efficient and scalable Multi-Agent Reinforcement Learning...

Paper Accepted at ICML Workshop on Unsupervised Reinforcement Learning

MASAI: Multi-agent Summative Assessment Improvement for Unsupervised Environment Design Reinforcement Learning agents require a distribution of environments for their policy to be trained on. The...

NSERC Discovery Grant Supports GAIDG Lab Research

The NSERC Discovery Grant has been awarded to the GAIDG Lab for the Diverse Synthetic Crowds in Media, Design, and Analysis research program. The goal of the proposed research is to radically...

See all news here..

Territory Acknowledgement

We acknowledge with respect the Lekwungen peoples on whose traditional territory the university stands and the Songhees, Esquimalt and W̱SÁNEĆ peoples whose historical relationships with the land continue to this day.

The GAIDG Lab is interested in broad ways of knowing and understanding and recognizes that ideas,  research, and the people involved in these may come from many different places and backgrounds. We also recognize that historically, and very much presently, work in the fields in and around Computer Science and particularly Machine Learning and Artificial Intelligence has had a role in and facilitated colonialism, racism, ableism, transphobia, and homophobia. Additionally, the computational resources required for modern AI, ML, and data mining have a direct impact on the environment. The GAIDG Lab is committed to addressing and reflecting on these issues in our work, hiring and training practices, our community output, and our outreach.

Contact

GAIDG Lab
Department of Computer Science
Room 648, Engineering and Computer Science (ECS) building
University of Victoria
Victoria, BC

bhaworth@uvic.ca

+1 250-472-5772