Albrecht, Stefano V

26 publications

TMLR 2025 Highway Graph to Accelerate Reinforcement Learning Zidu Yin, Zhen Zhang, Dong Gong, Stefano V Albrecht, Javen Qinfeng Shi
NeurIPS 2025 HyperMARL: Adaptive Hypernetworks for Multi-Agent RL Kale-ab Tessera, Arrasy Rahman, Amos Storkey, Stefano V. Albrecht
ICLR 2025 Online-to-Offline RL for Agent Alignment Xu Liu, Haobo Fu, Stefano V Albrecht, Qiang Fu, Shuai Li
ICLR 2025 Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning Samuel Garcin, Trevor McInroe, Pablo Samuel Castro, Christopher G. Lucas, David Abel, Prakash Panangaden, Stefano V Albrecht
AAAI 2024 Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning Guy Azran, Mohamad H. Danesh, Stefano V. Albrecht, Sarah Keren
ICML 2024 DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V Albrecht
TMLR 2024 Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning Trevor McInroe, Lukas Schäfer, Stefano V Albrecht
NeurIPS 2024 Skill-Aware Mutual Information Optimisation for Zero-Shot Generalisation in Reinforcement Learning Xuehui Yu, Mhairi Dunion, Xin Li, Stefano V. Albrecht
ICLR 2024 lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning Shangmin Guo, Yi Ren, Stefano V Albrecht, Kenny Smith
JMLR 2023 A General Learning Framework for Open Ad Hoc Teamwork Using Graph-Based Policy Learning Arrasy Rahman, Ignacio Carlucho, Niklas Höpner, Stefano V. Albrecht
TMLR 2023 Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity Arrasy Rahman, Elliot Fosong, Ignacio Carlucho, Stefano V Albrecht
NeurIPSW 2023 How the Level Sampling Process Impacts Zero-Shot Generalisation in Deep Reinforcement Learning Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V Albrecht
TMLR 2023 Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning Filippos Christianos, Georgios Papoudakis, Stefano V Albrecht
ICLR 2023 Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V Albrecht
NeurIPSW 2022 Enhancing Transfer of Reinforcement Learning Agents with Abstract Contextual Embeddings Guy Azran, Mohamad Hosein Danesh, Stefano V Albrecht, Sarah Keren
ICLR 2022 Expressivity of Emergent Languages Is a Trade-Off Between Contextual Complexity and Unpredictability Shangmin Guo, Yi Ren, Kory Wallace Mathewson, Simon Kirby, Stefano V Albrecht, Kenny Smith
NeurIPSW 2022 Learning Representations for Reinforcement Learning with Hierarchical Forward Models Trevor McInroe, Lukas Schäfer, Stefano V Albrecht
NeurIPSW 2022 Sample Relationships Through the Lens of Learning Dynamics with Label Information Shangmin Guo, Yi Ren, Stefano V Albrecht, Kenny Smith
NeurIPSW 2022 Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V Albrecht
ICMLW 2021 Decoupling Exploration and Exploitation in Reinforcement Learning Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V Albrecht
ICML 2021 Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing Filippos Christianos, Georgios Papoudakis, Muhammad A Rahman, Stefano V Albrecht
ICML 2021 Towards Open Ad Hoc Teamwork Using Graph-Based Policy Learning Muhammad A Rahman, Niklas Hopner, Filippos Christianos, Stefano V Albrecht
IJCAI 2017 Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract) Stefano V. Albrecht, Subramanian Ramamoorthy
JAIR 2016 Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks Stefano V. Albrecht, Subramanian Ramamoorthy
UAI 2015 Are You Doing What I Think You Are Doing? Criticising Uncertain Agent Models Stefano V. Albrecht, Subramanian Ramamoorthy
UAI 2014 On Convergence and Optimality of Best-Response Learning with Policy Types in Multiagent Systems Stefano V. Albrecht, Subramanian Ramamoorthy