Students

Using human data to create stronger opponents in Real Time Strategy Games

Use of Artificial General Intelligence techniques, with particular focus on Statistical Forward Planning, for automatic playtesting through the exploration of the skill/strategic space of the game.

Curiosity-driven PhD Candidate in Deep ((Multi-Agent) Reinforcement/Imitation) Learning. Especially interested in (Natural) Language Emergence & Grounding for Human-Machine Cooperation.

I’m interested in generating nonverbal behaviour models for social interactions in VR that builds into an emphatic and engaging virtual human (NPC).

PhD student working on applying rolling horizon evolutionary algorithms to general video game playing, for online planning in video games.

Human-Computer Interaction researcher focusing on what players enjoy about their opponents in strategy games, whether human or AI, and applying that to game design and AI construction.

General​ ​video​ ​game​ ​playing​ ​agents​ ​to​ ​evaluate​ ​automatic​ ​generated​ ​levels Procedural Content generation (PCG) refers to the generation of game content via automated processes. The validity of these artifacts should be checked to ensure their playability. Common approaches are game-specific and, although they ensure the playability of the generated content, they are limited by the game they are defined for....

Multidisciplinary researcher applying Multiagent Deep Reinforcement learning and Game theory to generate gameplaying AI agents for a wide variety of games.

Improving Game AI Design Using Adversarial Agents This project proposes a novel method for improving the quality of behaviour of human authored agents by pitting them against trained agents and observing what bad behaviours/exploits the trained agents reveal....

Evolving evolvable representations of neural networks

Games industry veteran and researcher with a bridging foot solidly placed in each camp. Gorm currently works on procedural content generation, virtual reality and mixed-initiative co-creative interfaces. He also has an interest in game design, participatory design, game jams and computer graphics.

Deep Learning for Procedural Content Generation in Virtual Environments Ryan Spick is a PhD student with a computer science background, working on methods to improve how content (models, terrain, assets etc.) is created with an autonomous focus, with the main focus on generative deep learning to augment real-world data through a series of neural network layers to learn unlying properties of these data....

PhD student working in analytics and machine learning for esports broadcast and understanding. In particular working with Weavr on various projects related to broadcast and learning tools for Dota 2.