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NIPS RL Trends & Apps 2014 : Novel Trends and Applications in Reinforcement Learning Workshop at NIPS 2014


When Dec 13, 2014 - Dec 13, 2014
Where Palais des Congrès de Montréal, Montrea
Submission Deadline Oct 17, 2014
Notification Due Nov 14, 2014
Categories    reinforcement learning   machine learning   control   robotics

Call For Papers

Novel Trends and Applications in Reinforcement Learning at NIPS 2014: Call for Contributions

8:30 am - 6:30 pm, Saturday, Dec 13 2014, Palais des Congrès de Montréal, Montreal, Quebec, Canada

Important Dates

Abstract submission (2+ pages in NIPS format): Oct 17, 2014, 11:59 PM UTC
Notification of acceptance: Oct 31, 2014
Workshop: Dec 13, 2014

Workshop Description

The last decade has witnessed a series of technological advances: social networks, cloud servers, personalized advertising, autonomous cars, personalized healthcare, robotics, security systems, just to name a few. These new technologies have in turn substantially reshaped our demands from adaptive reinforcement learning systems, defining novel yet urgent challenges. In response, a wealth of novel ideas and trends have emerged, tackling problems such as modelling rich and high-dimensional dynamics, life-long learning, resource-bounded planning, and multi-agent cooperation.

The objective of the workshop is to provide a platform for researchers from various areas (e.g., deep learning, game theory, robotics, computational neuroscience, information theory, Bayesian modelling) to disseminate and exchange ideas, evaluating their advantages and caveats. In particular, we will ask participants to address the following questions:

1) What is the future of reinforcement learning?
2) What are the most important challenges?
3) What tools do we need the most?

A final panel discussion will then review the provided answers and focus on elaborating a list of trends and future challenges. Recent advances will be presented in short talks and a poster session based on contributed material.

Call for Participation

We are seeking *two types* of contributions:

1) *Abstracts* on a broad range of topics in reinforcement learning and relevant applications. Abstracts should be (preferrably) two pages in NIPS format. All accepted abstracts will be presented as posters and considered for oral presentation.

2) *Expert opinions* (( 500 chars.) about the future of RL and its most important challenges. We seek to get a general picture of the state of RL. We will publish all selected opinions on our website, and they will provide the background material for our workshop.

Please visit our website at for submission instructions.

Confirmed Speakers

Emma Brunskill
Aldo Faisal
Vicenç Gómez
Daniel D. Lee
Gerhard Neumann
David Silver
Naftali Tishby
Brian Ziebart

Workshop Organizers

Csaba Szepesvari (University of Alebrta, Canada)
Marc Deisenroth (Imperial College London, UK)
Pedro A. Ortega (University of Pennsylvania, USA)
Sergey Levine (UC Berkeley, USA)

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