Escape the (Virtual) Room!

 

Natalia Mallia

Virtual Reality (VR) has created a whole new realm of experiences. By placing people into varied situations and environments, VR enables them not only to explore, but to challenge themselves and gain skills in ways never thought possible. With applications in medical and psychological treatment, VR is now being used to train surgeons, treat PTSD, and to help people understand what it’s like to be on the autism spectrum. The key to this application is VR’s ability to immerse its users. 

Many agree that immersion needs two key ingredients: a sense of presence and interaction with the environment. Interaction comes in three main forms. Selection is about differentiating between items in the environment. Navigation allows travelling from one point to another and observing the environment. Finally, manipulation lets users grab, move and rotate selectable items. In addition to this, VR applications need a setting. Supervised by Dr Vanessa Camilleri and Prof. Alexiei Dingli, I chose to use escape rooms (adventure games where multiple puzzles are solved to leave a room) to experiment with these interaction techniques. 

I used escape rooms because they’re highly interactive and naturally immersive systems. And since interaction isn’t a one-size-fits-all scenario, I also applied procedural content generation (PCG) techniques to create the escape rooms themselves.

People selected items using a reticle, a small circle in the middle of the screen which expands or contracts to indicate which objects they could interact with. They navigated the space by looking around through the VR headset and moving their joystick. They manipulated puzzles from a separate screen which I layered on top of the escape room. This allowed them to inspect objects to their heart’s content, while also reducing the amount of clutter in the room.

Since there was no previous work in PCG escape rooms, I had to pave my own way. I used a genetic algorithm, a machine learning algorithm that mimics evolution in biology to select the best solution to a problem, to determine which puzzles and items would be placed in the escape room. I also programmed the game to create the rest of the room, placing floors, ceilings, and everything else that the algorithm didn’t consider. This made the space look like it had been made by an actual person, despite being created through AI.

From the results gathered, most people found that the system allowed them to explore the VR environment in a very natural way. Players said that the room’s generated interaction was consistent, reliable, and fun. 

Understanding immersion is critical for VR’s future applications. If we can help people hone these techniques by creating a few games along the way—so be it!  

This research was carried out as part of a Bachelor of Artificial Intelligence at the Faculty of ICT, University of Malta

Author: Natalia Mallia

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An Automatically Tailored Experience

Digital games need to keep players engaged. Since games are interactive media, achieving this goal means that game designers need to anticipate player actions to create a pre-designed experience. Traditionally, developers have achieved this by restricting player freedom to a strict set of actions thereby curating player experience and ensuring the fun factor. However, games are taking a different route with more users making their own content (User Generated Content, UGC) through extensive creativity tools which make it hard to predict player experience.

Vincent E. Farrugia
Vincent E. Farrugia

To overcome these challenges Vincent E. Farrugia (supervised by Prof. Georgios N. Yannakakis), merged game design and artificial intelligence (AI). He developed a software framework for handling player engagement in environments which feature user generated content and groups. The three pronged solution tackles problems during game production, playing the game itself, and making sure the framework is sustainable. To maintain engagement within groups he analysed data for a particular person within the group but also patterns common across the whole group. Farrugia created software tools, autonomous AI aids, and tools to test and support the framework.

The software framework is made up of inter-operating modules. Firstly, an engagement policy module allows designers to specify theories to express their vision of positive game engagement. Player modelling then shapes this backbone to specific player engagement needs. The module can autonomously learn from player creations as reactions to game stimuli. Individual and group manager modules use this mixture of expert knowledge, AI learnt data, and player game-play history to automatically adapt game content to solve player engagement problems. This procedural content generation (PCG) is tailored for a specific player and time.

The framework’s abilities were showcased in a digital game also developed by Farrugia. Various technologies were incorporated to encourage player creativity in group sessions and to enhance networking. The setup also allowed the AI to quickly learn from each player via parallelism. Initial testing used a simulated environment with software agents. Preliminary testing on real players followed. The simulation was through a personality system to validate the underlying algorithms under various conditions. The resulting diverse game-play styles provide suggestions for AI model improvement. Farrugia is enthusiastic about future work for this AI framework and giving developers better tools to allow player creativity to flourish while maintaining positive game-play experiences. 

This research was performed as part of a Master of Science degree at the Institute of Digital Games, University of Malta. It was partly funded by the Strategic Educational Pathways Scholarship (Malta), which is part-financed by the European Union—European Social Fund (ESF) under Operational Programme II—Cohesion Policy 2007—2013, ‘Empowering People for More Jobs and a Better Quality of Life’.