PhD Students
- Steve James (2021) - Learning Portable Symbolic Representations
- Ofir Marom (2021) - Leveraging Prior Knowledge for Sample Efficient Reinforcement Learning
- Orhan Can Görür (2020) - Social Cobots: Anticipatory Decision-Making for Collaborative Robots with Extended Human Adaptation
- Adam Earle (2019) - Spectral Reinforcement Learning
- Ashley Kleinhans (2019) - Robotic grasping inspired by neuroscience using tools developed for deep learning
- Ritesh Ajoodha (2018) - Influence modelling and learning between dynamic Bayesian networks using score-based structure learning
- Ndivhuwo Makondo (2018) - Accelerating robot learning of motor skills with knowledge transfer
- Pravesh Ranchod (2018) - Skill Discovery from Multiple Related Demonstrators
MSc Students
- Tlou Bokola (2020) - Knowledge Transfer Using Model-based Deep Reinforcement Learning
- Roy Eyono (2020) - Learning to Backpropagate
- Yongama Feni (2020) - Evaluating the Reliability of Quantification Results
- Shahil Mawjee (2020) - Progressive option extraction with a curriculum of tasks
- Liron Mizrahi (2020) - Using social context for person re-identification
- Raesetje Sefala (2020) - Using satellite images and computer vision to study the evolution and effects of spatial apartheid in South Africa
- Isaac Tarume (2020) - Study of Anomaly Detection in Diverse Populations using Probabilistic Graphical Models
- Craig Bester (2019) - Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces
- Menzi Mthwecu (2019) - Efficient Search and Tracking for Non-Stationary Targets
- Benjamin van Niekerk (2019) - Learning Safe Predictive Control with Gaussian Processes
- Sicelukwanda Zwane (2019) - Using Mixture Density Networks to Model Continuous Action Priors
- Richard Fisher (2018) - Topology-inspired Probabilistic Path Replanning in Dynamic Environments
- Jason Perlow (2018) - Raw Material Selection for Object Construction
- Ntokozo Mabena (2017) - Accelerating Decision Making Under Partial Observability Using Learned Action Priors
- Michihisa Hiratsuka (2016) - Incremental Learning of Smoothed Dynamic Motion Primitives from Demonstration
- Steve James (2016) - The Effect of Simulation Bias on Action Selection in Monte Carlo Tree Search
- Phumlani Khoza (2016) - Electroencephalography brain computer interface using an asynchronous protocol
- Jeremy Lai Hong (2016) - Adaptive Knowledge Injection for Monte Carlo Tree Search for Imperfect Information Games