3 papers
cs.RO2026
Latent Cluster Analysis for Vision-Language-Action Models
Theodor Wulff, Sergio Lanza, Tamara Bila +3
Vision-Language-Action (VLA) Models are increasingly used in robotics for their ability to ground language and perception into action, yet the internal representations driving thei…
cs.RO2023
Safe Reinforcement Learning in a Simulated Robotic Arm
Luka Kovač, Igor Farkaš
Reinforcement learning (RL) agents need to explore their environments in order to learn optimal policies. In many environments and tasks, safety is of critical importance. The wide…
cs.AI2023
Self-supervised network distillation: an effective approach to exploration in sparse reward environments
Matej Pecháč, Michal Chovanec, Igor Farkaš
Reinforcement learning can solve decision-making problems and train an agent to behave in an environment according to a predesigned reward function. However, such an approach becom…