Online Resource Allocation in Edge Computing Using Distributed Bidding Approaches. - Caroline Rublein; Fidan Mehmeti; Mark Towers; Sebastian Stein 001; Thomas F. La Porta (MASS, 2021)

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. - Maxime Chevalier-Boisvert; Bolun Dai; Mark Towers; Rodrigo Perez-Vicente; Lucas Willems; Salem Lahlou; Suman Pal; Pablo Samuel Castro; Jordan K. Terry (NeurIPS, 2023)

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. - Maxime Chevalier-Boisvert; Bolun Dai; Mark Towers; Rodrigo de Lazcano; Lucas Willems; Salem Lahlou; Suman Pal; Pablo Samuel Castro; Jordan K. Terry (CoRR, 2023)

Explaining an Agent's Future Beliefs Through Temporally Decomposing Future Reward Estimators. - Mark Towers; Yali Du 001; Christopher T. Freeman; Timothy J. Norman (ECAI, 2024)

Temporal Explanations of Deep Reinforcement Learning Agents. - Mark Towers; Yali Du 001; Christopher T. Freeman; Timothy J. Norman (EXTRAAMAS, 2024)

Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning. - Shengyi Huang; Quentin Gallouédec; Florian Felten; Antonin Raffin; Rousslan Fernand Julien Dossa; Yanxiao Zhao; Ryan Sullivan; Viktor Makoviychuk; Denys Makoviichuk; Mohamad H. Danesh; Cyril Roumégous; Jiayi Weng; et al. (CoRR, 2024)

Gymnasium: A Standard Interface for Reinforcement Learning Environments. - Mark Towers; Ariel Kwiatkowski; Jordan K. Terry; John U. Balis; Gianluca De Cola; Tristan Deleu; Manuel Goulão; Andreas Kallinteris; Markus Krimmel; Arjun KG; Rodrigo Perez-Vicente; Andrea Pierré; et al. (CoRR, 2024)

Beyond The Rainbow: High Performance Deep Reinforcement Learning On A Desktop PC. - Tyler Clark; Mark Towers; Christine Evers; Jonathon Hare (CoRR, 2024)

Objective Metrics for Human-Subjects Evaluation in Explainable Reinforcement Learning. - Balint Gyevnar; Mark Towers (CoRR, 2025)