3 papers
cs.CV2026
FlexPath: Adapting Learned Connectivity Guidance to Path Preferences
Taehyoung Kim, Tim Schoenbrod, David Eckel +1
Recent learning-based path planners use neural networks to process occupancy representations and approximate heuristics for classical search algorithms, yielding near-optimal paths…
cs.LG2026
Hierarchical Lead Critic based Multi-Agent Reinforcement Learning
David Eckel, Henri MeeÃ
Cooperative Multi-Agent Reinforcement Learning (MARL) solves complex tasks that require coordination from multiple agents, but is often limited to either local (independent learnin…
cs.LG2024
Revisiting Safe Exploration in Safe Reinforcement learning
David Eckel, Baohe Zhang, Joschka Bödecker
Safe reinforcement learning (SafeRL) extends standard reinforcement learning with the idea of safety, where safety is typically defined through the constraint of the expected cost…