[agents] 2nd CfP: Future of Interactive Learning Machines Workshop @ NIPS 2016

[Kaushik Subramanian]

Hi Everyone,

We would like to invite submissions for the workshop on the Future of
Interactive Learning Machines (FILM) at NIPS 2016 in Barcelona, Spain in
December this year. The submission deadline is Oct 14th 2016 (less than two
weeks away). Please find the call for papers below. We look forward to your
submissions.

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NIPS 2016 Workshop: Future of Interactive Learning Machines
Barcelona, Spain
http://www.filmnips.com/
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Important Dates
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Paper submission deadline: *Oct 14th 2016*
Notification of acceptance: Oct 29th 2016
Camera-ready submission deadline: Nov 11th 2016
FILM workshop at NIPS 2016 in Barcelona, Spain: Dec 9th 2016

Invited Speakers
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Emma Brunskill, Carnegie Mellon University
Todd Gureckis, New York University
Ece Kamar, Microsoft Research
Matthew E. Taylor, Washington State University
Vladimir Vapnik, Columbia University and Facebook

Overview
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Interactive machine learning (IML) explores how intelligent agents solve a
task together, often focusing on adaptable collaboration over the course of
sequential decision making tasks. Past research in the field of IML has
investigated how autonomous agents can learn to solve problems more
effectively by making use of interactions with humans. Designing and
engineering fully autonomous agents is a difficult and sometimes
intractable challenge. As such, there is a compelling need for IML
algorithms that enable artificial and human agents to collaborate and solve
independent or shared goals. The range of real-world examples of IML spans
from web applications such as search engines, recommendation systems and
social media personalization, to dialog systems and embodied systems such
as industrial robots and household robotic assistants, and to medical
robotics (e.g. bionic limbs, assistive devices, and exoskeletons). As
intelligent systems become more common in industry and in everyday life,
the need for these systems to interact with and learn from the people
around them will also increase.

This workshop seeks to brings together experts in the fields of IML,
reinforcement learning (RL), human-computer interaction (HCI), robotics,
cognitive psychology and the social sciences to share recent advances and
explore the future of IML. Some questions of particular interest for this
workshop include: How can recent advancements in machine learning allow
interactive learning to be deployed in current real world applications? How
do we address the challenging problem of seamless communication between
autonomous agents and humans? How can we improve the ability to collaborate
safely and successfully across a diverse user set?

We hope that this workshop will produce several outcomes:

- A review of current algorithms and techniques for IML, and a focused
perspective on what is lacking
- A formalization of the main challenges for deploying modern interactive
learning algorithms in the real world
- A forum for interdisciplinary researchers to discuss open problems and
challenges, present new ideas on IML and plan for future collaborations

Relevant Topics
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- Human-robot interaction
- Collaborative and/or shared control
- Semi-supervised learning with human intervention
- Learning from demonstration, interaction and/or observation
- Reinforcement learning with human-in-the-loop
- Active learning, Preference learning
- Transfer learning (human-to-machine, machine-to-machine)
- Natural language processing for dialog systems
- Computer vision for human interaction with autonomous systems
- Transparency and feedback in machine learning
- Computational models of human teaching
- Intelligent personal assistants and dialog systems
- Adaptive user interfaces
- Brain-computer interfaces (e.g. human-semi-autonomous system interfaces)
- Intelligent medical robots (e.g. smart wheelchairs, prosthetics,
exoskeletons)

We seek broad participation from researchers in the fields of artificial
intelligence, machine learning, human-computer interaction, cognitive
science, robotics, intelligent interface design, adaptive systems and
related fields.

Submission Details
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We encourage submissions covering new ideas in interactive learning,
reports on research in progress as well as discussions of open problems and
challenges facing interactive machine learning. We are particularly
interested in research regarding the practical application of interactive
learning systems (for robotics, virtual agents, online education, dialog
systems, health care, security, transportation, etc.), and the ability of
these systems to handle the complexity of real world problems. We also
encourage submissions bringing perspectives from the fields of psychology
and social science, and from human computer interaction.

Authors are invited to submit long papers (8 pages for main text and 1 page
for references) or short papers (2 to 4 pages for main text and 1 page for
references) on research relevant to the theme of the workshop. The papers
should be formatted according to NIPS formatting guidelines and submitted
as a PDF document. All submissions are handled electronically through
EasyChair (https://easychair.org/conferences/?conf=filmnips2016).

Papers will be subject to a single-blind peer review, i.e. authors can keep
their names and affiliations on their submitted papers. Papers will be
evaluated based on originality, technical soundness, clarity and potential
impact on the field of interactive machine learning. Accepted papers will
be made publicly available on the workshop website. Accepted papers will be
presented as talks and/or posters at the workshop.

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Contact: If you have any questions, comments or concerns, please contact
the organizers at film.nips2016 at gmail.com.

Looking forward to seeing you in Barcelona!

- FILM Organizers