Advances in artificial intelligence are stimulating interest in neuroscience. However, most
attention is given to discrete tasks with simple action spaces, such as board games and …

Modeling human motor control and predicting how humans will move in novel environments
is a grand scientific challenge. Researchers in the fields of biomechanics and motor control …

The incredible feats of athleticism demonstrated by humans are made possible in part by a
vast repertoire of general-purpose motor skills, acquired through years of practice and …

Learning to combine control at the level of joint torques with longer-term goal-directed
behavior is a long-standing challenge for physically embodied artificial agents. Intelligent …

Marker-less 3D human motion capture from a single colour camera has seen significant
progress. However, it is a very challenging and severely ill-posed problem. In consequence …

Humans are able to perform a myriad of sophisticated tasks by drawing upon skills acquired
through prior experience. For autonomous agents to have this capability, they must be able …

Reinforcement learning offers a promising methodology for developing skills for simulated
characters, but typically requires working with sparse hand-crafted features. Building on …

We present a motion synthesis framework capable of producing a wide variety of important
human behaviors that have rarely been studied, including getting up from the ground …

In this paper we present a novel method for creating realistic, controllable motion. Given a
corpus of motion capture data, we automatically construct a directed graph called a motion …

Human characters with a broad range of natural looking and physically realistic behaviors
will enable the construction of compelling interactive experiences. In this paper, we develop …