Dr Robert Loftin

About

Robert received his PhD in Computer Science from North Carolina State University in 2019, under the supervision of Dave Roberts. His dissertation examined the types of latent knowledge conveyed by human-provided feedback and demonstrations, and developed interactive learning algorithms which leverage models of human behavior to extract this information. He received his Bachelor's in Computer Science from Georgia Tech in 2011. After completing his PhD, he did a two-year post-doc with Microsoft Research Cambridge, exploring the use of Reinforcement Learning and Interactive Learning in commercial game development. He also completed a post-doc at TU Delft with Frans Oliehoek, where he focused on applying game theory and multi-agent reinforcement learning to human-AI cooperation. Robert is curr

Selected publications

• Peng B, MacGlashan J, Loftin R, Littman ML, Roberts DL & Taylor ME (2018) Curriculum Design for Machine Learners in Sequential Decision Tasks. IEEE Transactions on Emerging Topics in Computational Intelligence, 2(4), 268-277.
• Loftin R, Peng B, MacGlashan J, Littman ML, Taylor ME, Huang J & Roberts DL (2016) Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. Autonomous Agents and Multi-Agent Systems, 30(1), 30-59.
• Loftin R, Bandyopadhyay S & Çelikok MM (2025) On the complexity of learning to cooperate in populations of socially rational agents. Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems (pp 233-241). Detroit, Michigan, USA, 19 May 2025 - 19 May 2025. View this article in WRRO
• Aydeniz AA, Marchesini E, Loftin R, Amato C & Tumer K (2025) Safe Entropic Agents under Team Constraints. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems Aamas (pp 2411-2413)
• Loftin R, Çelikok MM, van Hoof H, Kaski S & Oliehoek FA (2024) Uncoupled learning of differential Stackelberg equilibria with commitments. Proceedings of AAMAS-2024 (pp 1265-1273). Auckland, New Zealand, 6 May 2024 - 6 May 2024. View this article in WRRO
• Aydeniz AA, Marchesini E, Loftin R & Tumer K (2023) Entropy Maximization in High Dimensional Multiagent State Spaces. 2023 International Symposium on Multi-Robot and Multi-Agent Systems (MRS) (pp 92-99), 4 December 2023 - 5 December 2023.
• Aydeniz AA, Loftin R & Tumer K (2023) Novelty Seeking Multiagent Evolutionary Reinforcement Learning. Proceedings of the Genetic and Evolutionary Computation Conference (pp 402-410)
• Loftin R & Oliehoek FA (2022) On the impossibility of learning to cooperate with adaptive partner strategies in repeated games. Proceedings of the 39th International Conference on Machine Learning, Vol. 162 (pp 14197-14209). Baltimore, MD, USA View this article in WRRO
• Loftin R, Saha A, Devlin S & Hofmann K (2021) Strategically efficient exploration in competitive multi-agent reinforcement learning. Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence (UAI 2021), Vol. 161 (pp 1587-1596). Online, 27 July 2021 - 27 July 2021. View this article in WRRO
• Loftin R, Saha A, Devlin S & Hofmann K (2021) Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning. 37th Conference on Uncertainty in Artificial Intelligence Uai 2021 (pp 1587-1596)