[robotics-worldwide] [meetings] 2nd CFP AAAI-2019 Workshop on Games and Simulations for Artificial Intelligence

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[robotics-worldwide] [meetings] 2nd CFP AAAI-2019 Workshop on Games and Simulations for Artificial Intelligence

Marwan Mattar
We are pleased to announce the call for paper for the AAAI-2019 Workshop on
Games and Simulations for Artificial Intelligence that will be held on
January 27 or 28, 2019 in Honolulu, Hawaii. *Deadline for submission is
November 5, 2018.*

This will be a full-day workshop and will include a mix of invited
speakers, peer-reviewed papers (talks and poster sessions) and will
conclude with a panel discussion.

Information can be found on our website (updated regularly):


Over the past several years, games and simulations have become a powerful
tool for AI research. They have become the default testing grounds for new
algorithms thanks to platforms such as Mujoco, Arcade Learning Environment,
OpenAI Gym, VizDoom, DeepMind Lab, Facebook House3D, Allen Institute
AI2-Thor, Microsoft AirSim, General Video Game AI and Unity ML-Agents
toolkit. Additionally, they are a mechanism for generating large amounts of
training data for learning complex models for tasks such as 3D pose
estimation, physics modeling, natural language instruction following,
embodied question answering and robotics. Due to the physical and visual
realism of several of these platforms, complex models can be trained in a
virtual setting and then transferred to an agent or robot in the real world
with minor fine-tuning. Recent examples include learning dexterous
manipulation behaviors for a robotic hand and training self-driving cars.

The workshop aims to bring together researchers across artificial
intelligence interested in the use of games and simulation platforms. This
includes the creation of platforms, environments, data sets or benchmarks;
novel tasks and algorithms that leverage those platforms; adapting models
learned within those platforms for the real world where applicable.

We invite high-quality paper submissions on topics including, but not
limited to, the following:
- Novel simulation platforms, data sets and challenges for evaluating
algorithms. This includes games and environments with physical and
- Mechanisms for learning synthetic data set generation
- Novel tasks that can be solved using simulation platforms
- Algorithms for learning from large data sets generated by simulation
platforms. This includes distributed algorithms that can leverage multiple
simulation instances.
- Mechanisms for minimizing the reality gap between simulations and the
real world. This can be due to better adaptations and fine-tuning or
enabling more realistic simulation environments.

Important Dates
- Paper submission deadline: November 5, 2018
- Notification to authors: November 26, 2018
- Workshop Day: Either January 27, 2019 or January 28, 2019

- Marwan Mattar (Engineering Manager, Unity Technologies)
- Roozbeh Mottaghi (Research Scientist, Allen Institute for Artificial
- Julian Togelius (Associate Professor, New York University)
- Danny Lange (Vice-President of AI, Unity Technologies)

Instructions for Authors
Submissions of technical papers can be up to 8 pages excluding references
and appendices. Short or position papers of 2 to 4 pages are welcome. All
papers must be submitted in PDF format, using the AAAI-2019 author kit.
Papers will be peer-reviewed and selected for oral or poster presentations
at the workshop. Attendance is open to all, and at least one author of each
accepted submission must be present at the workshop.

Submission Link: https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_conferences_-3Fconf-3Dgamesim2019&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=ka7GPdokBQbjLhYJO1xafu3AFBpopCx5MIyAQE_xPnE&s=9TEm-0q1leJU0YO2yIG0PzvI8yyKvBRLWohKZ5bj9Vg&e=

As AAAI does not produce technical reports for its workshops, we will
arrange for the publication and distribution of the accepted papers. More
details will be provided as the submission deadline nears.
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