3 papers
cs.LG2026
Trust-Region Diffusion Policies for Massively Parallel On-Policy RL
Huy Le, Onur Celik, Denis Blessing +6
Reinforcement learning with massively parallel simulations has become a standard framework for developing robust, deployable policies; however, most existing approaches still rely…
cs.RO2026
Context-aware Learned Mesh-based Simulation via Trajectory-Level Meta-Learning
Philipp Dahlinger, Niklas Freymuth, Tai Hoang +4
Simulating object deformations is a critical challenge across many scientific domains, including robotics, manufacturing, and structural mechanics. Learned Graph Network Simulators…
cs.AI2025
Information-Theoretic Policy Pre-Training with Empowerment
Moritz Schneider, Robert Krug, Narunas Vaskevicius +3
Empowerment, an information-theoretic measure of an agent's potential influence on its environment, has emerged as a powerful intrinsic motivation and exploration framework for rei…