Jacopo Pierotti, Maximilian Kronmueller, Javier Alonso-Mora, J. Theresia van Essen, Wendelin Böhmer (2021), Reinforcement Learning for the Knapsack Problem, In AIRO Springer Series p.3-13, Springer Nature.

Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Böhmer, Shimon Whiteson (2021), Transient non-stationarity and generalisation in deep reinforcement learning.

Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Böhmer, Shimon Whiteson (2021), UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning, Marina Meila, Tong Zhang (Eds.), In Proceedings of the International Conference on Machine Learning (ICML) Volume 139 p.3930-3941.

Wendelin Böhmer, Vitaly Kurin, Shimon Whiteson (2020), Deep coordination graphs, Hal Daume, Aarti Singh (Eds.), In 37th International Conference on Machine Learning, ICML 2020 p.957-968, International Machine Learning Society (IMLS).

Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson (2020), Deep residual reinforcement learning, Bo An, Amal El Fallah Seghrouchni, Gita Sukthankar (Eds.), In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020 p.1611-1619, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N Siddharth, Wendelin Böhmer, Shimon Whiteson (2020), Multitask Soft Option Learning, In Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI) Volume 124 p.969-978.

Tabish Rashid, Bei Peng, Wendelin Böhmer, Shimon Whiteson (2020), Optimistic Exploration even with a Pessimistic Initialisation, In International Conference on Learning Representations (ICLR).

Wendelin Böhmer, Tabish Rashid, Shimon Whiteson (2019), Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning, In ICML em Exploration in Reinforcement Learning workshop Volume abs/1906.02138.

Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson (2019), Generalized off-policy actor-critic, In Advances in Neural Information Processing Systems.

Dongge Han, Wendelin Böhmer, Michael Wooldridge, Alex Rogers (2019), Multi-agent Hierarchical Reinforcement Learning with Dynamic Termination, Abhaya C. Nayak, Alok Sharma (Eds.), In PRICAI 2019 Volume 11671 p.80-92, Springer.