Advances in Machine Learning for Sensorimotor Control

NIPS 2013


Closed-loop control of systems based on sensor readings in uncertain domains is a hallmark of research in the Control, Artificial Intelligence, and Neuroscience communities. Various sensorimotor frameworks have been effective at controlling physical and biological systems, but many techniques rely on pre-specified models to derive useful policies. Advances in machine learning, including non-parametric Bayesian modeling/inference and reinforcement learning allow systems to learn better models and policies from data. However, incorporating modern machine learning techniques into sensorimotor control systems can be challenging due to the learner's underlying assumptions, the need to model uncertainty, and the scale of such problems. This workshop will bring together researchers from machine learning, control, and neuroscience that bridge this gap between effective planning systems and machine learning techniques to produce better sensorimotor control. The workshop will focus on machine learning for better models and policies for biological and physical systems with many sensors, including autonomous robots and vehicles, as well as complex real world systems, such as neural control or healthcare where actions may take place over a longer timescale.



Authors are encouraged to submit their related work to the workshop by 14th of October 11:59 PM PDT (UTC -7 hours) in NIPS format. Submissions should be a maximum of 8 pages with an extra page for references, though shorter papers are welcome as well. Submissions do not need to be anonymous. Papers can be submitted through the EasyChair website.

Authors of the selected papers will be notified to present their work through short presentations or posters.

- 8/20/13    Call for Papers for our workshop is out

- 9/13/13    Workshop date set: 9th December, 2013 (Monday)

- 10/9/13    Workshop Submission deadline extended to October 14th! (Monday)

- 10/23/13   Paper reviews and decisions will be mailed by October 31st

- 11/5/13   Accepted papers and tentative schedule posted