Stefano V. Albrecht

发表

Comparative evaluation of MAL algorithms in a diverse set of ad hoc team problems

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2012, AAMAS.

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

Subramanian Ramamoorthy, Stefano V. Albrecht, 2013, AAMAS.

Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence

Jacob W. Crandall, Ram Ramamoorthy, Stefano V. Albrecht, 2015, AAAI 2015.

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

Lukas Schäfer, Filippos Christianos, Stefano V. Albrecht, 2020, NeurIPS.

Reasoning about Unforeseen Possibilities During Policy Learning pdf

Alex Lascarides, Benjamin Rosman, Subramanian Ramamoorthy, 2018, ArXiv.

Belief and Truth in Hypothesised Behaviours

Jacob W. Crandall, Subramanian Ramamoorthy, Stefano V. Albrecht, 2015, Artif. Intell..

Reports of the AAAI 2014 Conference Workshops

Guy Van den Broeck, André da Motta Salles Barreto, Jenna Wiens, 2015, AI Mag..

Variational Autoencoders for Opponent Modeling in Multi-Agent Systems pdf

Stefano V. Albrecht, Georgios Papoudakis, Georgios Papoudakis, 2019, ArXiv.

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

Francisco Eiras, Subramanian Ramamoorthy, Majd Hawasly, 2020, IEEE Transactions on Robotics.

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

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2019, ArXiv.

An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types

Jacob W. Crandall, Subramanian Ramamoorthy, Stefano V. Albrecht, 2015, AAAI.

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

Jacob W. Crandall, Subramanian Ramamoorthy, Stefano V. Albrecht, 2015, AAAI 2015.

Quantum-Secure Authentication via Abstract Multi-Agent Interaction pdf

Ibrahim Ahmed, Josiah P. Hanna, Stefano V. Albrecht, 2020, ArXiv.

A Game-theoretic Model and Best-response Learning Method for Ad Hoc Coordination in Multiagent Systems (Extended Abstract)

Subramanian Ramamoorthy, Stefano V. Albrecht, 2013 .

Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012)

Ram Ramamoorthy, Stefano V. Albrecht, 2012, AAMAS 2012.

Reports of the 2016 AAAI Workshop Program

Bruno Bouchard, Parisa Kordjamshidi, Toby Walsh, 2016, AI Mag..

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

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2017, IJCAI.

Stabilizing Generative Adversarial Network Training: A Survey pdf

Stefano V. Albrecht, Maciej Wiatrak, 2019, ArXiv.

Interpretable Goal-based Prediction and Planning for Autonomous Driving

Francisco Eiras, Subramanian Ramamoorthy, Stefano V. Albrecht, 2020 .

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

Filippos Christianos, Stefano V. Albrecht, Arrasy Rahman, 2020, ICML.

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

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2014, UAI.

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

Filippos Christianos, Stefano V. Albrecht, Georgios Papoudakis, 2019, ArXiv.

Opponent Modelling with Local Information Variational Autoencoders pdf

Filippos Christianos, Stefano V. Albrecht, Georgios Papoudakis, 2020, ArXiv.

A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2013, AAMAS.

Exploiting Causality for Efficient Monitoring in POMDPs pdf

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2014, ArXiv.

Local Information Agent Modelling in Partially-Observable Environments

Filippos Christianos, Stefano V. Albrecht, Georgios Papoudakis, 2021 .

Utilising policy types for effective ad hoc coordination in multiagent systems

Stefano V. Albrecht, 2015 .

Twenty-Ninth AAAI Conference on Artificial Intelligence

Jacob W. Crandall, Ram Ramamoorthy, Stefano V. Albrecht, 2015, AAAI 2015.

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

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2015, UAI.

Artificial Intelligence Applied to Assistive Technologies and Smart Environments, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016

Eric Eaton, Toby Walsh, Francesca Rossi, 2016, AAAI Workshop: Artificial Intelligence Applied to Assistive Technologies and Smart Environments.

Comparative Evaluation of Multi-Agent Deep Reinforcement Learning Algorithms pdf

Lukas Schäfer, Filippos Christianos, Stefano V. Albrecht, 2020, ArXiv.

AAMAS '13 Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems

Ram Ramamoorthy, Stefano V. Albrecht, 2013, AAMAS 2013.

Stabilizing Generative Adversarial Networks: A Survey

Stefano V. Albrecht, Maciej Wiatrak, Andrew Nystrom, 2019 .

Reports from the 2015 AAAI Workshop Program

Bruno Bouchard, Parisa Kordjamshidi, Enrico Pontelli, 2015, AI Mag..

Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI-15)

Ram Ramamoorthy, Stefano V. Albrecht, 2015 .

Special issue on multiagent interaction without prior coordination: guest editorial

Peter Stone, Somchaya Liemhetcharat, Stefano V. Albrecht, 2016, Autonomous Agents and Multi-Agent Systems.

Special issue on autonomous agents modelling other agents: Guest editorial

Peter Stone, Michael P. Wellman, Stefano V. Albrecht, 2020, Artif. Intell..

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

Subramanian Ramamoorthy, Stefano V. Albrecht, S. Ramamoorthy, 2014, IJCAI.

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

Francisco Eiras, Subramanian Ramamoorthy, Majd Hawasly, 2020, ArXiv.

Integrating Planning and Interpretable Goal Recognition for Autonomous Driving pdf

Francisco Eiras, Subramanian Ramamoorthy, Stefano V. Albrecht, 2020, ArXiv.

Reasoning about Hypothetical Agent Behaviours and their Parameters

Peter Stone, Stefano V. Albrecht, P. Stone, 2017, AAMAS.

Reports on the 2015 AAAI workshop series

Eric Eaton, Gary F. Marcus, Cornelia Caragea, 2015 .

Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence

Ram Ramamoorthy, Stefano V. Albrecht, 2014 .

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

Peter Stone, Stefano V. Albrecht, P. Stone, 2017, Artif. Intell..

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

Simon Kirby, Kenny Smith, Shangmin Guo, 2021, ArXiv.

Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing

Filippos Christianos, Stefano V. Albrecht, Georgios Papoudakis, 2021, ICML.

Decoupling Exploration and Exploitation in Reinforcement Learning pdf

Lukas Schäfer, Filippos Christianos, Stefano V. Albrecht, 2021, ArXiv.

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

Stefano V. Albrecht, Cillian Brewitt, Balint Gyevnar, 2021, ArXiv.

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

Lukas Schäfer, Josiah P. Hanna, Stefano V. Albrecht, 2021, ArXiv.

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

Josiah P. Hanna, Stefano V. Albrecht, Ibrahim H. Ahmed, 2021, PAAMS.

GRIT: Fast, Interpretable, and Verifiable Goal Recognition with Learned Decision Trees for Autonomous Driving

Stefano V. Albrecht, Cillian Brewitt, Balint Gyevnar, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles

Francisco Eiras, Subramanian Ramamoorthy, Mihai Dobre, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

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

Lukas Schäfer, Stefano V. Albrecht, Trevor A. McInroe, 2021, ArXiv.

Agent Modelling under Partial Observability for Deep Reinforcement Learning

Stefano V. Albrecht, Georgios Papoudakis, Filippos Christianos, 2020, NeurIPS.

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

Stefano V. Albrecht, S. Ramamoorthy, 2017 .

Autonomous Driving with Interpretable Goal Recognition and Monte Carlo Tree Search

Stefano V. Albrecht, S. Ramamoorthy, M. Dobre, 2020 .

An Optimization-based Motion Planner for Safe Autonomous Driving

Stefano V. Albrecht, S. Ramamoorthy, Majd Hawasly, 2020 .

MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments

Stefano V. Albrecht, G. Muscato, S. Palazzo, 2022, 2205.08389.

Learning Representations for Control with Hierarchical Forward Models

Stefano V. Albrecht, Lukas Schafer, Trevor McInroe, 2022, 2206.11396.

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning

Josiah P. Hanna, Stefano V. Albrecht, K. Luck, 2022, 2207.05480.

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

Stefano V. Albrecht, A. Storkey, Filippos Christianos, 2022, ArXiv.

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

Shay B. Cohen, Christopher G. Lucas, Stefano V. Albrecht, 2022, ArXiv.

Learning Representations for Control with Hierarchical Forward Models

Stefano V. Albrecht, Trevor A. McInroe, Trevor McInroe, 2022, ArXiv.

Flash: Fast and Light Motion Prediction for Autonomous Driving with Bayesian Inverse Planning and Learned Motion Profiles

Stefano V. Albrecht, S. Ramamoorthy, M. Dobre, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning

Josiah P. Hanna, Stefano V. Albrecht, Trevor A. McInroe, 2022, ICLR.

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

Josiah P. Hanna, Stefano V. Albrecht, Lukas Schafer, 2021, NeurIPS.

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

Shay B. Cohen, Christopher G. Lucas, Stefano V. Albrecht, 2022, ArXiv.

Comparative Evaluation of Cooperative Multi-Agent Deep Reinforcement Learning Algorithms

Stefano V. Albrecht, Filippos Christianos, Georgios Papoudakis, 2021 .

Few-Shot Teamwork

Stefano V. Albrecht, Arrasy Rahman, Ignacio Carlucho, 2022, ArXiv.

NeurIPS 2022 Workshop on Deep Reinforcement Learning

Josiah P. Hanna, Stefano V. Albrecht, K. Luck, 2022 .

Sample Relationships through the Lens of Learning Dynamics with Label Information

Stefano V. Albrecht, Kenny Smith, Shangmin Guo, 2022 .

Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing

Stefano V. Albrecht, Filippos Christianos, Georgios Papoudakis, 2021, 2102.07475.

Local Information Opponent Modelling Using Variational Autoencoders.

Stefano V. Albrecht, Filippos Christianos, Georgios Papoudakis, 2020 .

Comparison of Multiagent Learning Algorithms in Ad Hoc Teams

Stefano V. Albrecht, 2011 .

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

Stefano V. Albrecht, M. Sridharan, Peter Stone, 2022, ArXiv.

Stabilizing Generative Adversarial Network Training: A Survey

Stefano V. Albrecht, Maciej Wiatrak, 2019, ArXiv.

Stabilizing Generative Adversarial Networks: A Survey

Stefano V. Albrecht, Andrew Nystrom, Maciej Wiatrak, 2019, 1910.00927.

MIDGARD: A Simulation Platform for Autonomous Navigation in Unstructured Environments

Stefano V. Albrecht, G. Muscato, S. Palazzo, 2022, ArXiv.

Deep Reinforcement Learning for Multi-Agent Interaction

Stefano V. Albrecht, Trevor A. McInroe, Filippos Christianos, 2022, AI Commun..

Revisiting the Gumbel-Softmax in MADDPG

Stefano V. Albrecht, Filippos Christianos, C. Tilbury, 2023, ArXiv.

A Survey of Ad Hoc Teamwork Research

Stefano V. Albrecht, M. Sridharan, Peter Stone, 2022, EUMAS.

Learning Complex Teamwork Tasks using a Sub-task Curriculum

Stefano V. Albrecht, Arrasy Rahman, Ignacio Carlucho, 2023, arXiv.org.

Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks

Stefano V. Albrecht, Filippos Christianos, Georgios Papoudakis, 2020, NeurIPS Datasets and Benchmarks.

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

Stefano V. Albrecht, Georgios Papoudakis, Lukas Schafer, 2022, ArXiv.

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

Shay B. Cohen, Christopher G. Lucas, Stefano V. Albrecht, 2023, ArXiv.

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

Stefano V. Albrecht, Peter Karkus, M. Pavone, 2022, 2023 IEEE International Conference on Robotics and Automation (ICRA).

DiPA: Diverse and Probabilistically Accurate Interactive Prediction

Stefano V. Albrecht, S. Ramamoorthy, Majd Hawasly, 2022, arXiv.org.

Interpretable Goal-based Prediction and Planning for Autonomous Driving

Stefano V. Albrecht, S. Ramamoorthy, M. Dobre, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Causal Explanations for Stochastic Sequential Multi-Agent Decision-Making

Shay B. Cohen, Christopher G. Lucas, Stefano V. Albrecht, 2023, 2302.10809.

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

Stefano V. Albrecht, J. Ser, Esther Villar-Rodriguez, 2023, ArXiv.

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

Stefano V. Albrecht, Yali Du, D. Mguni, 2023, ArXiv.

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

Stefano V. Albrecht, Filippos Christianos, Georgios Papoudakis, 2022, ArXiv.

Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration

Josiah P. Hanna, Stefano V. Albrecht, Filippos Christianos, 2021, AAMAS.

Revisiting the Gumbel-Softmax in MADDPG

Stefano V. Albrecht, Filippos Christianos, C. Tilbury, 2023, ArXiv.

SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning

Stefano V. Albrecht, Filippos Christianos, Adam Michalski, 2023, ArXiv.

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

Stefano V. Albrecht, Georgios Papoudakis, Lukas Schafer, 2022, ArXiv.

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

Stefano V. Albrecht, S. Kirby, Kenny Smith, 2021, ICLR.

Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity

Stefano V. Albrecht, Arrasy Rahman, Ignacio Carlucho, 2022, 2207.14138.

Verifiable Goal Recognition for Autonomous Driving with Occlusions

Stefano V. Albrecht, Massimiliano Tamborski, Cillian Brewitt, 2022, arXiv.org.

DiPA: Probabilistic Multi-Modal Interactive Prediction for Autonomous Driving

Stefano V. Albrecht, S. Ramamoorthy, Majd Hawasly, 2022, IEEE Robotics and Automation Letters.

Multi-agent systems research in the United Kingdom

Stefano V. Albrecht, M. Wooldridge, 2022, AI Commun..

Contextual Pre-Planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning

Stefano V. Albrecht, Mohamad H. Danesh, Sarah Keren, 2023, AAAI.

Decoupling Exploration and Exploitation in Reinforcement Learning

Stefano V. Albrecht, Filippos Christianos, J. Hanna, 2021, ArXiv.

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

Shay B. Cohen, Christopher G. Lucas, Stefano V. Albrecht, 2023, AAMAS.

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

Josiah P. Hanna, Stefano V. Albrecht, Trevor A. McInroe, 2023, arXiv.org.

NeurIPS 2022 Workshop on Deep Reinforcement Learning

Stefano V. Albrecht, K. Luck, Reinforcement Learning, 2022 .

Special issue on multiagent interaction without prior coordination: guest editorial

Stefano V. Albrecht, P. Stone, Somchaya Liemhetcharat, 2017, Autonomous Agents and Multi-Agent Systems.

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

Stefano V. Albrecht, Arrasy Rahman, Niklas Höpner, 2022, J. Mach. Learn. Res..

Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning

Stefano V. Albrecht, Trevor A. McInroe, Lukas Schäfer, 2022, 2206.11396.

Flash: Fast and Light Motion Prediction for Autonomous Driving with Bayesian Inverse Planning and Learned Motion Profiles

Stefano V. Albrecht, S. Ramamoorthy, M. Dobre, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Learning Complex Teamwork Tasks Using a Given Sub-task Decomposition

Stefano V. Albrecht, Arrasy Rahman, Ignacio Carlucho, 2023, 2302.04944.

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

Stefano V. Albrecht, Filippos Christianos, Georgios Papoudakis, 2022, ArXiv.

Generating Diverse Teammates to Train Robust Agents For Ad Hoc Teamwork

Stefano V. Albrecht, Arrasy Rahman, Ignacio Carlucho, 2023 .

Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning

Josiah P. Hanna, Stefano V. Albrecht, Trevor A. McInroe, 2022, ICLR.