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07/02/2023
Effects of Explanation Specificity on Passengers in Autonomous Driving
The nature of explanations provided by an explainable AI algorithm has b...
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06/15/2023
A Framework for Learning from Demonstration with Minimal Human Effort
We consider robot learning in the context of shared autonomy, where cont...
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02/06/2023
DITTO: Offline Imitation Learning with World Models
We propose DITTO, an offline imitation learning algorithm which uses wor...
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11/30/2022
One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning
Offline reinforcement learning (RL) is suitable for safety-critical doma...
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10/08/2022
VP-STO: Via-point-based Stochastic Trajectory Optimization for Reactive Robot Behavior
Achieving reactive robot behavior in complex dynamic environments is sti...
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04/26/2022
RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning
Offline reinforcement learning (RL) aims to find near-optimal policies f...
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04/17/2022
Beta Residuals: Improving Fault-Tolerant Control for Sensory Faults via Bayesian Inference and Precision Learning
Model-based fault-tolerant control (FTC) often consists of two distinct ...
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10/25/2021
Lexicographic Optimisation of Conditional Value at Risk and Expected Value for Risk-Averse Planning in MDPs
Planning in Markov decision processes (MDPs) typically optimises the exp...
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09/23/2021
Risk-Aware Motion Planning in Partially Known Environments
Recent trends envisage robots being deployed in areas deemed dangerous t...
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09/13/2021
Towards Stochastic Fault-tolerant Control using Precision Learning and Active Inference
This work presents a fault-tolerant control scheme for sensory faults in...
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09/13/2021
On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic Inference
Previous work on planning as active inference addresses finite horizon p...
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04/05/2021
Fault-tolerant Control of Robot Manipulators with Sensory Faults using Unbiased Active Inference
This work presents a novel fault-tolerant control scheme based on active...
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02/10/2021
Risk-Averse Bayes-Adaptive Reinforcement Learning
In this work, we address risk-averse Bayesadaptive reinforcement learnin...
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12/08/2020
Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes
The parameters for a Markov Decision Process (MDP) often cannot be speci...
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05/12/2020
Active Inference for Integrated State-Estimation, Control, and Learning
This work presents an approach for control, state-estimation and learnin...
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03/09/2020
Convex Hull Monte-Carlo Tree Search
This work investigates Monte-Carlo planning for agents in stochastic env...
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11/12/2019
Mixed-Initiative variable autonomy for remotely operated mobile robots
This paper presents an expert-guided Mixed-Initiative (MI) variable-auto...
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07/13/2018
Artificial Intelligence for Long-Term Robot Autonomy: A Survey
Autonomous systems will play an essential role in many applications acro...
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03/07/2018
Simultaneous Task Allocation and Planning Under Uncertainty
We propose novel techniques for task allocation and planning in multi-ro...
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02/28/2017