Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …

Multibody software designed for mechanical engineering has been successfully employed
in biomedical research for many years. For real time operation some biomedical researchers …

Movement is fundamental to human and animal life, emerging through interaction of
complex neural, muscular, and skeletal systems. Study of movement draws from and …

Computational modeling and simulation of neuromusculoskeletal (NMS) systems enables
researchers and clinicians to study the complex dynamics underlying human and animal …

Muscle-driven simulations of human and animal motion are widely used to complement
physical experiments for studying movement dynamics. Musculotendon models are an …

The lengths and velocities of muscle fibers have a dramatic effect on muscle force
generation. It is unknown, however, whether the lengths and velocities of lower limb muscle …

We present a technique for automatically synthesizing walking and running controllers for
physically-simulated 3D humanoid characters. The sagittal hip, knee, and ankle degrees-of …

Wearable robotic devices can restore and enhance mobility. There is growing interest in
designing devices that reduce the metabolic cost of walking; however, designers lack …

Tools have been used for millions of years to augment the capabilities of the human body,
allowing us to accomplish tasks that would otherwise be difficult or impossible. Powered …

Reinforcement Learning is an area of Machine Learning focused on how agents can be
trained to make sequential decisions, and achieve a particular goal within an arbitrary …