59 citations · 457 across the 92 of their papers we have counts for
10 papers · 1 filter
Active Altruism Learning and Information Sufficiency for Autonomous Driving
Jack Geary, Henry Gouk, Subramanian Ramamoorthy
Safe interaction between vehicles requires the ability to choose actions that reveal the preferences of the other vehicles. Since exploratory actions often do not directly contribu…
Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles
Xin Du, Subramanian Ramamoorthy, Wouter Duivesteijn +2
Local decision rules are commonly understood to be more explainable, due to the local nature of the patterns involved. With numerical optimization methods such as gradient boosting…
Automated Testing with Temporal Logic Specifications for Robotic Controllers using Adaptive Experiment Design
Craig Innes, Subramanian Ramamoorthy
Many robot control scenarios involve assessing system robustness against a task specification. If either the controller or environment are composed of "black-box" components with u…
Attainment Regions in Feature-Parameter Space for High-Level Debugging in Autonomous Robots
Simón C. Smith, Subramanian Ramamoorthy
Understanding a controller's performance in different scenarios is crucial for robots that are going to be deployed in safety-critical tasks. If we do not have a model of the dynam…
Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles
Josiah P. Hanna, Arrasy Rahman, Elliot Fosong +5
Recognising the goals or intentions of observed vehicles is a key step towards predicting the long-term future behaviour of other agents in an autonomous driving scenario. When the…
Learning Time-Invariant Reward Functions through Model-Based Inverse Reinforcement Learning
Todor Davchev, Sarah Bechtle, Subramanian Ramamoorthy +1
Inverse reinforcement learning is a paradigm motivated by the goal of learning general reward functions from demonstrated behaviours. Yet the notion of generality for learnt costs…
Automatic Synthesis of Experiment Designs from Probabilistic Environment Specifications
Craig Innes, Yordan Hristov, Georgios Kamaras +1
This paper presents an extension to the probabilistic programming language ProbRobScene, allowing users to automatically synthesize uniform experiment designs directly from environ…
Building Affordance Relations for Robotic Agents - A Review
Paola Ardón, Èric Pairet, Katrin S. Lohan +2
Affordances describe the possibilities for an agent to perform actions with an object. While the significance of the affordance concept has been previously studied from varied pers…
Learning data association without data association: An EM approach to neural assignment prediction
Michael Burke, Subramanian Ramamoorthy
Data association is a fundamental component of effective multi-object tracking. Current approaches to data-association tend to frame this as an assignment problem relying on gating…
Formation Control for UAVs Using a Flux Guided Approach
John Hartley, Hubert P. H. Shum, Edmond S. L. Ho +2
Existing studies on formation control for unmanned aerial vehicles (UAV) have not considered encircling targets where an optimum coverage of the target is required at all times. Su…