Decoding the brain: From neural representations to mechanistic models
A central principle in neuroscience is that neurons within the brain act in concert to produce
perception, cognition, and adaptive behavior. Neurons are organized into specialized brain …
perception, cognition, and adaptive behavior. Neurons are organized into specialized brain …
Latent exploration for reinforcement learning
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 …
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
Abstract Machine learning methods have a groundbreaking impact in many application
domains, but their application on real robotic platforms is still limited. Despite the many …
domains, but their application on real robotic platforms is still limited. Despite the many …
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 …
Contrastive abstraction for reinforcement learning
Learning agents with reinforcement learning is difficult when dealing with long trajectories
that involve a large number of states. To address these learning problems effectively, the …
that involve a large number of states. To address these learning problems effectively, the …
Curriculum Learning Influences the Emergence of Different Learning Trends
R Mir, P Ojaghi, A Erwin, A Marjaninejad… - 2024 IEEE-RAS 23rd …, 2024 - ieeexplore.ieee.org
Reinforcement learning (RL) algorithms are traditionally evaluated and compared by their
learning trends (ie, average performance) over trials and time. However, the presence of a …
learning trends (ie, average performance) over trials and time. However, the presence of a …
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 …
MyoChallenge 2024: Physiological Dexterity and Agility in Bionic Humans
Limb loss represents a traumatic and destabilizing event in human life, significantly
impacting an individual's quality of life and independence. Advancements in bionic …
impacting an individual's quality of life and independence. Advancements in bionic …