Stefano V. Albrecht

Trans. Mach. Learn. Res., 2024

Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Highway Graph to Accelerate Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problems.

[BibT_eX]

[DOI]

CoRR, 2024

LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots.

[BibT_eX]

[DOI]

CoRR, 2024

Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review.

[BibT_eX]

[DOI]

CoRR, 2024

ICED: Zero-Shot Transfer in Reinforcement Learning via In-Context Environment Design.

[BibT_eX]

[DOI]

CoRR, 2024

Sample Relationship from Learning Dynamics Matters for Generalisation.

[BibT_eX]

[DOI]

CoRR, 2024

Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning.

[BibT_eX]

RLJ, 2024

Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras.

[BibT_eX]

Mhairi Dunion

RLJ, 2024

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Causal Explanations for Sequential Decision-Making in Multi-Agent Systems.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Learning Complex Teamwork Tasks using a Given Sub-task Decomposition.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

DiPA: Probabilistic Multi-Modal Interactive Prediction for Autonomous Driving.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2023

A General Learning Framework for Open Ad Hoc Teamwork Using Graph-based Policy Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Is Feedback All You Need? Leveraging Natural Language Feedback in Goal-Conditioned Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning.

[BibT_eX]

[DOI]

Amos J. Storkey

CoRR, 2023

How the level sampling process impacts zero-shot generalisation in deep reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2023

SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Adam Michalski

CoRR, 2023

Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments.

[BibT_eX]

[DOI]

Alain Andres

Esther Villar-Rodriguez

Javier Del Ser

CoRR, 2023

Revisiting the Gumbel-Softmax in MADDPG.

[BibT_eX]

[DOI]

Callum Rhys Tilbury

CoRR, 2023

Causal Social Explanations for Stochastic Sequential Multi-Agent Decision-Making.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Complex Teamwork Tasks using a Sub-task Curriculum.

[BibT_eX]

[DOI]

CoRR, 2023

Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Cillian Brewitt

Cheng Wang

IROS, 2023

Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

A Two-Stage Optimization-Based Motion Planner for Safe Urban Driving.

[BibT_eX]

[DOI]

Francisco Eiras

Majd Hawasly

IEEE Trans. Robotics, 2022

Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers.

[BibT_eX]

[DOI]

CoRR, 2022

DiPA: Diverse and Probabilistically Accurate Interactive Prediction.

[BibT_eX]

[DOI]

CoRR, 2022

Towards Robust Ad Hoc Teamwork Agents By Creating Diverse Training Teammates.

[BibT_eX]

[DOI]

CoRR, 2022

Few-Shot Teamwork.

[BibT_eX]

[DOI]

CoRR, 2022

Cooperative Marine Operations via Ad Hoc Teams.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Verifiable Goal Recognition for Autonomous Driving with Occlusions.

[BibT_eX]

[DOI]

Cillian Brewitt

CoRR, 2022

Learning Representations for Control with Hierarchical Forward Models.

[BibT_eX]

[DOI]

CoRR, 2022

A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning.

[BibT_eX]

[DOI]

Balint Gyevnar

CoRR, 2022

MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments.

[BibT_eX]

[DOI]

CoRR, 2022

A Survey of Ad Hoc Teamwork: Definitions, Methods, and Open Problems.

[BibT_eX]

[DOI]

CoRR, 2022

Perspectives on the system-level design of a safe autonomous driving stack.

[BibT_eX]

[DOI]

AI Commun., 2022

Multi-agent systems research in the United Kingdom.

[BibT_eX]

[DOI]

Michael J. Wooldridge

AI Commun., 2022

Deep reinforcement learning for multi-agent interaction.

[BibT_eX]

[DOI]

Giuseppe Vecchio

Cheng Wang

AI Commun., 2022

Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Shangmin Guo

Yi Ren

Kory Wallace Mathewson

Simon Kirby

Kenny Smith

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Survey of Ad Hoc Teamwork Research.

[BibT_eX]

[DOI]

Proceedings of the Multi-Agent Systems - 19th European Conference, 2022

Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

Robust On-Policy Data Collection for Data-Efficient Policy Evaluation.

[BibT_eX]

[DOI]

CoRR, 2021

Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Decoupling Exploration and Exploitation in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability.

[BibT_eX]

[DOI]

CoRR, 2021

GRIT: Verifiable Goal Recognition for Autonomous Driving using Decision Trees.

[BibT_eX]

[DOI]

Cillian Brewitt

Balint Gyevnar

CoRR, 2021

Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Interpretable Goal-based Prediction and Planning for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Quantum-Secure Authentication via Abstract Multi-Agent Interaction.

[BibT_eX]

[DOI]

Ibrahim Ahmed

Josiah P. Hanna

CoRR, 2020

Open Ad Hoc Teamwork using Graph-based Policy Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Opponent Modelling with Local Information Variational Autoencoders.

[BibT_eX]

[DOI]

CoRR, 2020

Comparative Evaluation of Multi-Agent Deep Reinforcement Learning Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

Integrating Planning and Interpretable Goal Recognition for Autonomous Driving.

[BibT_eX]

[DOI]

CoRR, 2020

A Two-Stage Optimization Approach to Safe-by-Design Planning for Autonomous Driving.

[BibT_eX]

[DOI]

Francisco Eiras

Majd Hawasly

CoRR, 2020

Variational Autoencoders for Opponent Modeling in Multi-Agent Systems.

[BibT_eX]

[DOI]

CoRR, 2020

Special issue on autonomous agents modelling other agents: Guest editorial.

[BibT_eX]

[DOI]

Michael P. Wellman

Artif. Intell., 2020

Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Maciej Wiatrak

CoRR, 2019

E-HBA: Using Action Policies for Expert Advice and Agent Typification.

[BibT_eX]

[DOI]

Jacob W. Crandall

CoRR, 2019

Comparative Evaluation of Multiagent Learning Algorithms in a Diverse Set of Ad Hoc Team Problems.

[BibT_eX]

[DOI]

CoRR, 2019

Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Reasoning about Unforeseen Possibilities During Policy Learning.

[BibT_eX]

[DOI]

Craig Innes

Alex Lascarides

Benjamin Rosman

CoRR, 2018

Autonomous agents modelling other agents: A comprehensive survey and open problems.

[BibT_eX]

[DOI]

Artif. Intell., 2018

2017

Special issue on multiagent interaction without prior coordination: guest editorial.

[BibT_eX]

[DOI]

Somchaya Liemhetcharat

Auton. Agents Multi Agent Syst., 2017

Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Reasoning about Hypothetical Agent Behaviours and their Parameters.

[BibT_eX]

[DOI]

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

2016

Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2016

Reports of the 2016 AAAI Workshop Program.

[BibT_eX]

[DOI]

AI Mag., 2016

Belief and truth in hypothesised behaviours.

[BibT_eX]

[DOI]

Jacob W. Crandall

Stefano Vittorino Albrecht

Artif. Intell., 2016

2015

Utilising policy types for effective ad hoc coordination in multiagent systems.

[BibT_eX]

[DOI]

PhD thesis, 2015

Reports from the 2015 AAAI Workshop Program.

[BibT_eX]

[DOI]

AI Mag., 2015

Reports of the AAAI 2014 Conference Workshops.

[BibT_eX]

[DOI]

AI Mag., 2015

Are You Doing What I Think You Are Doing? Criticising Uncertain Agent Models.

[BibT_eX]

[DOI]

Stefano Vittorino Albrecht

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.

[BibT_eX]

[DOI]

Jacob William Crandall

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Exploiting Causality for Efficient Monitoring in POMDPs.

[BibT_eX]

[DOI]

CoRR, 2014

On Convergence and Optimality of Best-Response Learning with Policy Types in Multiagent Systems.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

2013

Ad hoc coordination in multiagent systems with applications to human-machine interaction.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]