Lukas Schäfer

According to our database, Lukas Schäfer authored at least 16 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Visual Encoders for Data-Efficient Imitation Learning in Modern Video Games.

Lukas Schäfer, Logan Jones, Anssi Kanervisto, Yuhan Cao, Tabish Rashid, Raluca Georgescu, David Bignell, Siddhartha Sen, Andrea Treviño Gavito, Sam Devlin

CoRR, 2023

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

Alain Andres, Lukas Schäfer, Esther Villar-Rodriguez, Stefano V. Albrecht, Javier Del Ser

CoRR, 2023

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

Lukas Schäfer, Oliver Slumbers, Stephen McAleer, Yali Du, Stefano V. Albrecht, David Mguni

CoRR, 2023

2022

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

Aleksandar Krnjaic, Jonathan D. Thomas, Georgios Papoudakis, Lukas Schäfer, Peter Börsting, Stefano V. Albrecht

CoRR, 2022

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

Lukas Schäfer, Filippos Christianos, Amos J. Storkey, Stefano V. Albrecht

CoRR, 2022

Learning Representations for Control with Hierarchical Forward Models.

Trevor McInroe, Lukas Schäfer, Stefano V. Albrecht

CoRR, 2022

Deep reinforcement learning for multi-agent interaction.

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

AI Commun., 2022

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

Rujie Zhong, Duohan Zhang, Lukas Schäfer, Stefano V. Albrecht, Josiah Hanna

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Decoupled Reinforcement Learning to Stabilise Intrinsically-Motivated Exploration.

Lukas Schäfer, Filippos Christianos, Josiah P. Hanna, Stefano V. Albrecht

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

Task Generalisation in Multi-Agent Reinforcement Learning.

Lukas Schäfer

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

2021

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

Rujie Zhong, Josiah P. Hanna, Lukas Schäfer, Stefano V. Albrecht

CoRR, 2021

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

Trevor McInroe, Lukas Schäfer, Stefano V. Albrecht

CoRR, 2021

Decoupling Exploration and Exploitation in Reinforcement Learning.

Lukas Schäfer, Filippos Christianos, Josiah Hanna, Stefano V. Albrecht

CoRR, 2021

Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks.

Georgios Papoudakis, Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Comparative Evaluation of Multi-Agent Deep Reinforcement Learning Algorithms.

Georgios Papoudakis, Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht

CoRR, 2020

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

Filippos Christianos, Lukas Schäfer, Stefano V. Albrecht

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020