2025
Using offline data to speed up Reinforcement Learning in procedurally generated environments.
Neurocomputing, 2025
LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots.
Proceedings of the 31st International Conference on Computational Linguistics, 2025
2024
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review.
IEEE Trans. Intell. Transp. Syst., December, 2024
Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning.
Trans. Mach. Learn. Res., 2024
Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning.
CoRR, 2024
HyperMARL: Adaptive Hypernetworks for Multi-Agent RL.
CoRR, 2024
Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning.
CoRR, 2024
Highway Graph to Accelerate Reinforcement Learning.
CoRR, 2024
Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problems.
CoRR, 2024
ICED: Zero-Shot Transfer in Reinforcement Learning via In-Context Environment Design.
CoRR, 2024
Sample Relationship from Learning Dynamics Matters for Generalisation.
CoRR, 2024
Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning.
RLJ, 2024
Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras.
RLJ, 2024
Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers.
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Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024
DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
MIDGARD: A Robot Navigation Simulator for Outdoor Unstructured Environments.
Proceedings of the European Robotics Forum 2024, 2024
Causal Explanations for Sequential Decision-Making in Multi-Agent Systems.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
Learning Complex Teamwork Tasks using a Given Sub-task Decomposition.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity.
Trans. Mach. Learn. Res., 2023
Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning.
Trans. Mach. Learn. Res., 2023
DiPA: Probabilistic Multi-Modal Interactive Prediction for Autonomous Driving.
IEEE Robotics Autom. Lett., 2023
A General Learning Framework for Open Ad Hoc Teamwork Using Graph-based Policy Learning.
J. Mach. Learn. Res., 2023
Is Feedback All You Need? Leveraging Natural Language Feedback in Goal-Conditioned Reinforcement Learning.
CoRR, 2023
Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning.
CoRR, 2023
How the level sampling process impacts zero-shot generalisation in deep reinforcement learning.
CoRR, 2023
SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning.
CoRR, 2023
Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments.
CoRR, 2023
Revisiting the Gumbel-Softmax in MADDPG.
CoRR, 2023
Causal Social Explanations for Stochastic Sequential Multi-Agent Decision-Making.
CoRR, 2023
Learning Complex Teamwork Tasks using a Sub-task Curriculum.
CoRR, 2023
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning.
CoRR, 2023
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Verifiable Goal Recognition for Autonomous Driving with Occlusions.
IROS, 2023
Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
A Two-Stage Optimization-Based Motion Planner for Safe Urban Driving.
IEEE Trans. Robotics, 2022
Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers.
CoRR, 2022
DiPA: Diverse and Probabilistically Accurate Interactive Prediction.
CoRR, 2022
Towards Robust Ad Hoc Teamwork Agents By Creating Diverse Training Teammates.
CoRR, 2022
Cooperative Marine Operations via Ad Hoc Teams.
CoRR, 2022
Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learning.
CoRR, 2022
Verifiable Goal Recognition for Autonomous Driving with Occlusions.
CoRR, 2022
Learning Representations for Control with Hierarchical Forward Models.
CoRR, 2022
A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning.
CoRR, 2022
MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments.
CoRR, 2022
A Survey of Ad Hoc Teamwork: Definitions, Methods, and Open Problems.
CoRR, 2022
Perspectives on the system-level design of a safe autonomous driving stack.
AI Commun., 2022
Multi-agent systems research in the United Kingdom.
AI Commun., 2022
Deep reinforcement learning for multi-agent interaction.
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AI Commun., 2022
Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Flash: Fast and Light Motion Prediction for Autonomous Driving with Bayesian Inverse Planning and Learned Motion Profiles.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022
Expressivity of Emergent Languages is a Trade-off between Contextual Complexity and Unpredictability.
Proceedings of the Tenth International Conference on Learning Representations, 2022
A Survey of Ad Hoc Teamwork Research.
Proceedings of the Multi-Agent Systems - 19th European Conference, 2022
Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022
2021
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation.
CoRR, 2021
Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning.
CoRR, 2021
Decoupling Exploration and Exploitation in Reinforcement Learning.
CoRR, 2021
Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability.
CoRR, 2021
GRIT: Verifiable Goal Recognition for Autonomous Driving using Decision Trees.
CoRR, 2021
Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction.
Proceedings of the Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection, 2021
Agent Modelling under Partial Observability for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous Driving.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021
Interpretable Goal-based Prediction and Planning for Autonomous Driving.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Quantum-Secure Authentication via Abstract Multi-Agent Interaction.
CoRR, 2020
Open Ad Hoc Teamwork using Graph-based Policy Learning.
CoRR, 2020
Opponent Modelling with Local Information Variational Autoencoders.
CoRR, 2020
Comparative Evaluation of Multi-Agent Deep Reinforcement Learning Algorithms.
CoRR, 2020
Integrating Planning and Interpretable Goal Recognition for Autonomous Driving.
CoRR, 2020
A Two-Stage Optimization Approach to Safe-by-Design Planning for Autonomous Driving.
CoRR, 2020
Variational Autoencoders for Opponent Modeling in Multi-Agent Systems.
CoRR, 2020
Special issue on autonomous agents modelling other agents: Guest editorial.
Artif. Intell., 2020
Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
Stabilizing Generative Adversarial Network Training: A Survey.
CoRR, 2019
E-HBA: Using Action Policies for Expert Advice and Agent Typification.
CoRR, 2019
Comparative Evaluation of Multiagent Learning Algorithms in a Diverse Set of Ad Hoc Team Problems.
CoRR, 2019
Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning.
CoRR, 2019
2018
Reasoning about Unforeseen Possibilities During Policy Learning.
CoRR, 2018
Autonomous agents modelling other agents: A comprehensive survey and open problems.
Artif. Intell., 2018
2017
Special issue on multiagent interaction without prior coordination: guest editorial.
Auton. Agents Multi Agent Syst., 2017
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract).
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Reasoning about Hypothetical Agent Behaviours and their Parameters.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017
2016
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks.
J. Artif. Intell. Res., 2016
Reports of the 2016 AAAI Workshop Program.
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AI Mag., 2016
Belief and truth in hypothesised behaviours.
Artif. Intell., 2016
2015
Utilising policy types for effective ad hoc coordination in multiagent systems.
PhD thesis, 2015
Reports from the 2015 AAAI Workshop Program.
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AI Mag., 2015
Reports of the AAAI 2014 Conference Workshops.
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AI Mag., 2015
Are You Doing What I Think You Are Doing? Criticising Uncertain Agent Models.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015
An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Exploiting Causality for Efficient Monitoring in POMDPs.
CoRR, 2014
On Convergence and Optimality of Best-Response Learning with Policy Types in Multiagent Systems.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014
2013
Ad hoc coordination in multiagent systems with applications to human-machine interaction.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2013
A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2013
2012
Comparative evaluation of MAL algorithms in a diverse set of ad hoc team problems.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012