IJCAI-20MAPFWorkshop

webmaster: Sven Koenig

IJCAI-20 Workshop on Multi-Agent Path Finding

Welcome!

Multi-Agent Path Finding (MAPF) is the problem of computing collision-free paths for a team of agents from their current locations to given destinations in a known environment. Application examples include autonomous aircraft towing vehicles, automated warehouse systems, office robots, and game characters in video games. Solving the MAPF problem optimally is NP-hard for many objectives, such as minimizing the sum of the travel costs or the makespan, and can even be NP-hard to approximate. Yet, practical systems must find high-quality collision-free paths for the agents quickly because shorter paths result in higher throughput or lower operating costs (since fewer agents are required).

In recent years, many researchers have explored different variants of the MAPF problem as well as different approaches with different properties. Also, different applications have been studied in artificial intelligence, robotics, and theoretical computer science. The purpose of this workshop is to bring these researchers together to present their research, discuss future research directions, and cross-fertilize the different communities. Researchers and practitioners whose research might apply to MAPF or who might be able to use MAPF techniques in their research are welcome.

Program and Schedule
TBA

Invited Talks
TBA

Organizing Committee

  • Edward Lam, Monash University, (edward.lam@monash.edu)
  • Graeme Gange, Monash University, (Graeme.Gange@monash.edu)
  • Jiaoyang Li, University of Southern California, (jiaoyanl@usc.edu)
  • Dor Atzmon, Ben-Gurion University, (dorat@post.bgu.ac.il)
  • Thayne Walker, University of Denver, (thayne.walker@du.edu)

PC Members

  • Roman Barták, Charles University
  • Eli Boyarski, Ben-Gurion University of the Negev
  • Ariel Felner, Ben-Gurion University of the Negev
  • Daniel Harabor, Monash University
  • Wolfgang Hoenig, California Institute of Technology
  • Sven Koenig, University of Southern California
  • T. K. Satish Kumar, University of Southern California
  • Hang Ma, Simon Fraser University
  • Roni Stern, Ben Gurion University of the Negev
  • Pavel Surynek, Czech Technical University in Prague
  • Glenn Wagner, Carnegie Mellon University
  • Han Zhang, University of Southern California

All submissions that relate to collision-free path planning or navigation for multiple agents are welcome, including but not limited to:

  • Search-, rule-, reduction-, reactive-, and learning-based MAPF planners
  • Combination of MAPF and task allocation/scheduling
  • Combination of MAPF and execution monitoring
  • Variants and generalizations of the MAPF problem
  • Application domains for MAPF planners
  • Actual applications of MAPF planners
  • Customization of MAPF planners for actual robots (including kinematic constraints)
  • Standardization of MAPF terminology and benchmarks

Submissions can contain relevant work in all possible stages, including work that was recently published, is under submission elsewhere, was only recently finished, or is still ongoing. Authors of papers published or under submission elsewhere are encouraged to submit these papers or short versions (including abstracts) of them to the workshop to educate other researchers about their work, as long as resubmissions are clearly labeled to avoid copyright violations. Position papers and surveys are also welcome. Submissions will go through a light review process to ensure a fit with the topic of the workshop and acceptable quality. Non-archival workshop notes will be produced containing the material presented at the workshop.

Important dates

  • Paper submission deadline: 23:59 on September 4th, 2020 (UTC-12)
  • Paper notification: September 25th, 2020
  • Final version: December 14th, 2020
  • Workshop: January 2021

Information for authors
Submission page: https://easychair.org/conferences/?conf=womapf20
Format: Any format is acceptable.
Page limitation: There is no limit on the number of pages.


(last updated in 2019)