2 papers
cs.RO2026
Fast and Near-Optimal Collision-Free Robot Scheduling On Paths
Duncan Adamson, Nathan Flaherty, Igor Potapov +2
In this paper, we address the problem of scheduling a set of robots to complete tasks in a laboratory environment, modelled as a graph, while avoiding collisions. We analyze the dy…
cs.LG2025
MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
Elena Zamaraeva, Christopher M. Collins, George R. Darling +8
Geometry optimization of atomic structures is a common and crucial task in computational chemistry and materials design. Following the learning to optimize paradigm, we propose a n…