arXiv:2608. 16666v1 Announce Type: new Abstract: This paper presents Chronocooked, a reinforcement learning (RL) benchmark suite for studying implicit interval timing in RL agents.
By Amrapali Pednekar, Alvaro Garrido-Perez, Yara Khaluf, Pieter Simoens
arXiv:2607. 20656v1 Announce Type: cross Abstract: Effective decision-making in complex and changing environments requires balancing short-term and long-term consequences.
By Manoosh Samiei, Doina Precup, Paul Masset
arXiv:2608. 11511v1 Announce Type: cross Abstract: In sequential decision making, an agent typically observes its environment and acts at every timestep.
By Christopher Watson, Arjun Krishna, Dinesh Jayaraman, Rajeev Alur
arXiv:2605. 11484v2 Announce Type: replace Abstract: Task completion in digital and physical environments increasingly involves complex temporal interaction, where actions and observations unfold over different time scales rather than align with fixed observation--action steps.
By Jialian Li, Yuchen Cao, Junhong Liu, Weiran Guo, Xutao Wang, Jiaming Song, Jiahao Zhang, Jie Chen
arXiv:2608. 13625v1 Announce Type: new Abstract: Signal temporal logic (STL) provides a formal language for specifying real-time properties of real-valued observations, along with a quantitative robustness score for monitoring satisfaction.
By Alper Kamil Bozkurt, Shangtong Zhang, Yuichi Motai
Deliberating takes time. In real-time settings, that time is not free.