Latent exploration for reinforcement learning
AS Chiappa, A Marin Vargas… - Advances in Neural …, 2024 - proceedings.neurips.cc
Abstract In Reinforcement Learning, agents learn policies by exploring and interacting with
the environment. Due to the curse of dimensionality, learning policies that map high …
the environment. Due to the curse of dimensionality, learning policies that map high …
Curriculum Is More Influential Than Haptic Information During Reinforcement Learning of Object Manipulation Against Gravity
P Ojaghi, R Mir, A Marjaninejad, A Erwin… - arXiv preprint arXiv …, 2024 - arxiv.org
Learning to lift and rotate objects with the fingertips is necessary for autonomous in-hand
dexterous manipulation. In our study, we explore the impact of various factors on successful …
dexterous manipulation. In our study, we explore the impact of various factors on successful …
Acquiring musculoskeletal skills with curriculum-based reinforcement learning
Efficient, physiologically-detailed musculoskeletal simulators and powerful learning
algorithms provide new computational tools to tackle the grand challenge of understanding …
algorithms provide new computational tools to tackle the grand challenge of understanding …