2 papers
cs.LG2025
Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks
Muthukumar Pandaram, Jakob Hollenstein, David Drexel +3
The use of learned dynamics models, also known as world models, can improve the sample efficiency of reinforcement learning. Recent work suggests that the underlying causal graphs…
cs.RO2024
Investigating the Benefits of Nonlinear Action Maps in Data-Driven Teleoperation
Michael Przystupa, Gauthier Gidel, Matthew E. Taylor +3
As robots become more common for both able-bodied individuals and those living with a disability, it is increasingly important that lay people be able to drive multi-degree-of-free…