Stefano V. Albrecht

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 103

Top Venues

Publications

Dongge Han, Trevor McInroe, Adam Jelley, Stefano V. Albrecht, Peter Bell, Amos J. Storkey
LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots. CoRR (2024)
Balint Gyevnar, Cheng Wang, Christopher G. Lucas, Shay B. Cohen, Stefano V. Albrecht
Causal Explanations for Sequential Decision-Making in Multi-Agent Systems. AAMAS (2024)
Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning. AAAI (2024)
Zidu Yin, Zhen Zhang, Dong Gong, Stefano V. Albrecht, Javen Shi
Highway Graph to Accelerate Reinforcement Learning. CoRR (2024)
Shangmin Guo, Yi Ren, Stefano V. Albrecht, Kenny Smith
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning. ICLR (2024)
Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V. Albrecht
ICED: Zero-Shot Transfer in Reinforcement Learning via In-Context Environment Design. CoRR (2024)
Mhairi Dunion, Stefano V. Albrecht
Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras. CoRR (2024)
Sarah Keren, Chaimaa Essayeh, Stefano V. Albrecht, Thomas Mortsyn
Multi-Agent Reinforcement Learning for Energy Networks: Computational Challenges, Progress and Open Problems. CoRR (2024)
Trevor McInroe, Lukas Schäfer, Stefano V. Albrecht
Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning. Trans. Mach. Learn. Res. 2024 (2024)
Shangmin Guo, Yi Ren, Stefano V. Albrecht, Kenny Smith
Sample Relationship from Learning Dynamics Matters for Generalisation. CoRR (2024)
Elliot Fosong, Arrasy Rahman, Ignacio Carlucho, Stefano V. Albrecht
Learning Complex Teamwork Tasks using a Given Sub-task Decomposition. AAMAS (2024)
Xuehui Yu, Mhairi Dunion, Xin Li, Stefano V. Albrecht
Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning. CoRR (2024)
Anton Kuznietsov, Balint Gyevnar, Cheng Wang, Steven Peters, Stefano V. Albrecht
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review. CoRR (2024)
Adam Michalski, Filippos Christianos, Stefano V. Albrecht
SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning. CoRR (2023)
Elliot Fosong, Arrasy Rahman, Ignacio Carlucho, Stefano V. Albrecht
Learning Complex Teamwork Tasks using a Sub-task Curriculum. CoRR (2023)
Trevor McInroe, Stefano V. Albrecht, Amos J. Storkey
Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning. CoRR (2023)
Alain Andres, Lukas Schäfer, Esther Villar-Rodriguez, Stefano V. Albrecht, Javier Del Ser
Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments. CoRR (2023)
Callum Rhys Tilbury, Filippos Christianos, Stefano V. Albrecht
Revisiting the Gumbel-Softmax in MADDPG. CoRR (2023)
Lukas Schäfer, Oliver Slumbers, Stephen McAleer, Yali Du, Stefano V. Albrecht, David Mguni
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning. CoRR (2023)
Balint Gyevnar, Cheng Wang, Christopher G. Lucas, Shay B. Cohen, Stefano V. Albrecht
Causal Social Explanations for Stochastic Sequential Multi-Agent Decision-Making. CoRR (2023)
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah Hanna, Stefano V. Albrecht
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. NeurIPS (2023)
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning. CoRR (2023)
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning. ICLR (2023)
Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning. CoRR (2023)
Anthony Knittel, Majd Hawasly, Stefano V. Albrecht, John Redford, Subramanian Ramamoorthy
DiPA: Probabilistic Multi-Modal Interactive Prediction for Autonomous Driving. IEEE Robotics Autom. Lett. 8 (8) (2023)
Arrasy Rahman, Elliot Fosong, Ignacio Carlucho, Stefano V. Albrecht
Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity. Trans. Mach. Learn. Res. 2023 (2023)
Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V. Albrecht
How the level sampling process impacts zero-shot generalisation in deep reinforcement learning. CoRR (2023)
Filippos Christianos, Georgios Papoudakis, Stefano V. Albrecht
Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Filippos Christianos, Péter Karkus, Boris Ivanovic, Stefano V. Albrecht, Marco Pavone
Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models. ICRA (2023)
Sabrina McCallum, Max Taylor-Davies, Stefano V. Albrecht, Alessandro Suglia
Is Feedback All You Need? Leveraging Natural Language Feedback in Goal-Conditioned Reinforcement Learning. CoRR (2023)
Cillian Brewitt, Massimiliano Tamborski, Cheng Wang, Stefano V. Albrecht
Verifiable Goal Recognition for Autonomous Driving with Occlusions. IROS (2023)
Lukas Schäfer, Filippos Christianos, Josiah P. Hanna, Stefano V. Albrecht
Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration. AAMAS (2022)
Arrasy Rahman, Ignacio Carlucho, Niklas Höpner, Stefano V. Albrecht
A General Learning Framework for Open Ad Hoc Teamwork Using Graph-based Policy Learning. CoRR (2022)
Giuseppe Vecchio, Simone Palazzo, Dario C. Guastella, Ignacio Carlucho, Stefano V. Albrecht, Giovanni Muscato, Concetto Spampinato
MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments. CoRR (2022)
Majd Hawasly, Jonathan Sadeghi, Morris Antonello, Stefano V. Albrecht, John Redford, Subramanian Ramamoorthy
Perspectives on the system-level design of a safe autonomous driving stack. AI Commun. 35 (4) (2022)
Rujie Zhong, Duohan Zhang, Lukas Schäfer, Stefano V. Albrecht, Josiah Hanna
Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning. NeurIPS (2022)
Aleksandar Krnjaic, Jonathan D. Thomas, Georgios Papoudakis, Lukas Schäfer, Peter Börsting, Stefano V. Albrecht
Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers. CoRR (2022)
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Elliot Fosong, William Macke, Mohan Sridharan, Peter Stone, Stefano V. Albrecht
A Survey of Ad Hoc Teamwork: Definitions, Methods, and Open Problems. CoRR (2022)
Morris Antonello, Mihai Dobre, Stefano V. Albrecht, John Redford, Subramanian Ramamoorthy
Flash: Fast and Light Motion Prediction for Autonomous Driving with Bayesian Inverse Planning and Learned Motion Profiles. CoRR (2022)
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Elliot Fosong, William Macke, Mohan Sridharan, Peter Stone, Stefano V. Albrecht
A Survey of Ad Hoc Teamwork Research. EUMAS (2022)
Morris Antonello, Mihai Dobre, Stefano V. Albrecht, John Redford, Subramanian Ramamoorthy
Flash: Fast and Light Motion Prediction for Autonomous Driving with Bayesian Inverse Planning and Learned Motion Profiles. IROS (2022)
Mhairi Dunion, Trevor McInroe, Kevin Luck, Josiah Hanna, Stefano V. Albrecht
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning. CoRR (2022)
Trevor McInroe, Lukas Schäfer, Stefano V. Albrecht
Learning Representations for Control with Hierarchical Forward Models. CoRR (2022)
Francisco Eiras, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy
A Two-Stage Optimization-Based Motion Planner for Safe Urban Driving. IEEE Trans. Robotics 38 (2) (2022)
Filippos Christianos, Georgios Papoudakis, Stefano V. Albrecht
Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning. CoRR (2022)
Majd Hawasly, Jonathan Sadeghi, Morris Antonello, Stefano V. Albrecht, John Redford, Subramanian Ramamoorthy
Perspectives on the System-level Design of a Safe Autonomous Driving Stack. CoRR (2022)
Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho, Filippos Christianos, Mhairi Dunion, Elliot Fosong, Samuel Garcin, Shangmin Guo, Balint Gyevnar, Trevor McInroe, Georgios Papoudakis, Arrasy Rahman, Lukas Schäfer, Massimiliano Tamborski, Giuseppe Vecchio, Cheng Wang, Stefano V. Albrecht
Deep Reinforcement Learning for Multi-Agent Interaction. CoRR (2022)
Stefano V. Albrecht, Michael J. Wooldridge
Multi-agent systems research in the United Kingdom. AI Commun. 35 (4) (2022)
Cillian Brewitt, Massimiliano Tamborski, Stefano V. Albrecht
Verifiable Goal Recognition for Autonomous Driving with Occlusions. CoRR (2022)
Balint Gyevnar, Massimiliano Tamborski, Cheng Wang, Christopher G. Lucas, Shay B. Cohen, Stefano V. Albrecht
A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning. CoRR (2022)
Filippos Christianos, Péter Karkus, Boris Ivanovic, Stefano V. Albrecht, Marco Pavone
Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models. CoRR (2022)
Arrasy Rahman, Elliot Fosong, Ignacio Carlucho, Stefano V. Albrecht
Towards Robust Ad Hoc Teamwork Agents By Creating Diverse Training Teammates. CoRR (2022)
Anthony Knittel, Majd Hawasly, Stefano V. Albrecht, John Redford, Subramanian Ramamoorthy
DiPA: Diverse and Probabilistically Accurate Interactive Prediction. CoRR (2022)
Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho, Filippos Christianos, Mhairi Dunion, Elliot Fosong, Samuel Garcin, Shangmin Guo, Balint Gyevnar, Trevor McInroe, Georgios Papoudakis, Arrasy Rahman, Lukas Schäfer, Massimiliano Tamborski, Giuseppe Vecchio, Cheng Wang, Stefano V. Albrecht
Deep reinforcement learning for multi-agent interaction. AI Commun. 35 (4) (2022)
Shangmin Guo, Yi Ren, Kory Wallace Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith
Expressivity of Emergent Languages is a Trade-off between Contextual Complexity and Unpredictability. ICLR (2022)
Lukas Schäfer, Filippos Christianos, Amos J. Storkey, Stefano V. Albrecht
Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement Learning. CoRR (2022)
Elliot Fosong, Arrasy Rahman, Ignacio Carlucho, Stefano V. Albrecht
Few-Shot Teamwork. CoRR (2022)
Ignacio Carlucho, Arrasy Rahman, William Ard, Elliot Fosong, Corina Barbalata, Stefano V. Albrecht
Cooperative Marine Operations via Ad Hoc Teams. CoRR (2022)
Cillian Brewitt, Balint Gyevnar, Stefano V. Albrecht
GRIT: Verifiable Goal Recognition for Autonomous Driving using Decision Trees. CoRR (2021)
Ibrahim Ahmed, Josiah P. Hanna, Elliot Fosong, Stefano V. Albrecht
Towards Quantum-Secure Authentication and Key Agreement via Abstract Multi-Agent Interaction. PAAMS (2021)
Filippos Christianos, Georgios Papoudakis, Muhammad A. Rahman, Stefano V. Albrecht
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing. ICML (2021)
Rujie Zhong, Josiah P. Hanna, Lukas Schäfer, Stefano V. Albrecht
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation. CoRR (2021)
Muhammad A. Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning. ICML (2021)
Trevor McInroe, Lukas Schäfer, Stefano V. Albrecht
Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning. CoRR (2021)
Josiah P. Hanna, Arrasy Rahman, Elliot Fosong, Francisco Eiras, Mihai Dobre, John Redford, Subramanian Ramamoorthy, Stefano V. Albrecht
Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles. IROS (2021)
Stefano V. Albrecht, Cillian Brewitt, John Wilhelm, Balint Gyevnar, Francisco Eiras, Mihai Dobre, Subramanian Ramamoorthy
Interpretable Goal-based Prediction and Planning for Autonomous Driving. ICRA (2021)
Georgios Papoudakis, Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks. NeurIPS Datasets and Benchmarks (2021)
Josiah P. Hanna, Arrasy Rahman, Elliot Fosong, Francisco Eiras, Mihai Dobre, John Redford, Subramanian Ramamoorthy, Stefano V. Albrecht
Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles. CoRR (2021)
Shangmin Guo, Yi Ren, Kory W. Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith
Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability. CoRR (2021)
Georgios Papoudakis, Filippos Christianos, Stefano V. Albrecht
Agent Modelling under Partial Observability for Deep Reinforcement Learning. NeurIPS (2021)
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht
Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing. CoRR (2021)
Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V. Albrecht
Decoupling Exploration and Exploitation in Reinforcement Learning. CoRR (2021)
Henry Pulver, Francisco Eiras, Ludovico Carozza, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving. IROS (2021)
Cillian Brewitt, Balint Gyevnar, Samuel Garcin, Stefano V. Albrecht
GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous Driving. IROS (2021)
Henry Pulver, Francisco Eiras, Ludovico Carozza, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving. CoRR (2020)
Ibrahim Ahmed, Josiah P. Hanna, Stefano V. Albrecht
Quantum-Secure Authentication via Abstract Multi-Agent Interaction. CoRR (2020)
Stefano V. Albrecht, Cillian Brewitt, John Wilhelm, Francisco Eiras, Mihai Dobre, Subramanian Ramamoorthy
Integrating Planning and Interpretable Goal Recognition for Autonomous Driving. CoRR (2020)
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Open Ad Hoc Teamwork using Graph-based Policy Learning. CoRR (2020)
Georgios Papoudakis, Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht
Comparative Evaluation of Multi-Agent Deep Reinforcement Learning Algorithms. CoRR (2020)
Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht
Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning. CoRR (2020)
Stefano V. Albrecht, Peter Stone, Michael P. Wellman
Special issue on autonomous agents modelling other agents: Guest editorial. Artif. Intell. 285 (2020)
Francisco Eiras, Majd Hawasly, Stefano V. Albrecht, Subramanian Ramamoorthy
A Two-Stage Optimization Approach to Safe-by-Design Planning for Autonomous Driving. CoRR (2020)
Georgios Papoudakis, Filippos Christianos, Stefano V. Albrecht
Opponent Modelling with Local Information Variational Autoencoders. CoRR (2020)
Georgios Papoudakis, Stefano V. Albrecht
Variational Autoencoders for Opponent Modeling in Multi-Agent Systems. CoRR (2020)
Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht
Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning. NeurIPS (2020)
Georgios Papoudakis, Filippos Christianos, Arrasy Rahman, Stefano V. Albrecht
Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning. CoRR (2019)
Stefano V. Albrecht, Subramanian Ramamoorthy
Comparative Evaluation of Multiagent Learning Algorithms in a Diverse Set of Ad Hoc Team Problems. CoRR (2019)
Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
E-HBA: Using Action Policies for Expert Advice and Agent Typification. CoRR (2019)
Stefano V. Albrecht, Subramanian Ramamoorthy
Are You Doing What I Think You Are Doing? Criticising Uncertain Agent Models. CoRR (2019)
Stefano V. Albrecht, Peter Stone
Reasoning about Hypothetical Agent Behaviours and their Parameters. CoRR (2019)
Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types. CoRR (2019)
Maciej Wiatrak, Stefano V. Albrecht
Stabilizing Generative Adversarial Network Training: A Survey. CoRR (2019)
Stefano V. Albrecht, Subramanian Ramamoorthy
On Convergence and Optimality of Best-Response Learning with Policy Types in Multiagent Systems. CoRR (2019)
Stefano V. Albrecht, Subramanian Ramamoorthy
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract). CoRR (2019)
Craig Innes, Alex Lascarides, Stefano V. Albrecht, Subramanian Ramamoorthy, Benjamin Rosman
Reasoning about Unforeseen Possibilities During Policy Learning. CoRR (2018)
Stefano V. Albrecht, Peter Stone
Autonomous agents modelling other agents: A comprehensive survey and open problems. Artif. Intell. 258 (2018)
Stefano V. Albrecht, Peter Stone
Reasoning about Hypothetical Agent Behaviours and their Parameters. AAMAS (2017)
Stefano V. Albrecht, Subramanian Ramamoorthy
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract). IJCAI (2017)
Stefano V. Albrecht, Peter Stone
Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems. CoRR (2017)
Stefano V. Albrecht, Somchaya Liemhetcharat, Peter Stone
Special issue on multiagent interaction without prior coordination: guest editorial. Auton. Agents Multi Agent Syst. 31 (4) (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Stefano V. Albrecht