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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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05/26/2023
Formal Modelling for Multi-Robot Systems Under Uncertainty
Purpose of Review: To effectively synthesise and analyse multi-robot beh...
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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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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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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
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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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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03/07/2018