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Comparing Synthetic Tabular Data Generation Between a Probabilistic Model and a Deep Learning Model for Education Use Cases
The ability to generate synthetic data has a variety of use cases across different domains. In education research, there is a growing …
Herkulaas Combrink
,
Vukosi Marivate
,
Benjamin Rosman
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Real Time In-Game Playstyle Classification Using A Hybrid Probabilistic Supervised Learning Approach
In interactive digital media, such as video games, bringing about an adaptive or personalised experience requires a mechanism for …
Lindsay John Arendse
,
Branden Ingram
,
Benjamin Rosman
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Project
Reinforcement Learning in Education: A Multi-Armed Bandit Approach
Advances in reinforcement learning research have demonstrated the ways in which different agent-based models can learn how to optimally …
Herkulaas Combrink
,
Vukosi Marivate
,
Benjamin Rosman
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Improving Reinforcement Learning with Ensembles of Different Learners
Different reinforcement learning (RL) methods exist to address the problem of combining multiple different learners to generate a …
Gerrie Crafford
,
Benjamin Rosman
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Reducing the Planning Horizon through Reinforcement Learning
Planning is a computationally expensive process, which can limit the reactivity of autonomous agents. Planning problems are usually …
Logan Dunbar
,
Benjamin Rosman
,
Anthony G. Cohn
,
Matteo Leonetti
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Improved Action Prediction through Multiple Model Processing of Player Trajectories
Action prediction in video games is the process of extracting useful information in order to predict the future actions of a player. …
Branden Ingram
,
Benjamin Rosman
,
Clint van Alten
,
Richard Klein
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Project
Play-style Identification through Deep Unsupervised Clustering of Trajectories
In any game, play-style is a concept that describes the technique and strategy employed by a player to achieve a goal. Being able to …
Branden Ingram
,
Benjamin Rosman
,
Clint van Alten
,
Richard Klein
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Project
Analyzing Reinforcement Learning Algorithms for Nitrogen Fertilizer Management in Simulated Crop Growth
Establishing intelligent crop management techniques for preserving the soil, while providing next-generational food supply for an …
Michael Vogt
,
Benjamin Rosman
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Combining Evolutionary Search with Behaviour Cloning for Procedurally Generated Content
In this work, we consider the problem of procedural content generation for video game levels. Prior approaches have relied on …
Nicholas Muir
,
Steven James
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Project
Procedural Content Generation using Neuroevolution and Novelty Search for Diverse Video Game Levels
Procedurally generated video game content has the potential to drastically reduce the content creation budget of game developers and …
Michael Beukman
,
Christopher Cleghorn
,
Steven James
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