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<p><b style="font-weight:normal;"
id="docs-internal-guid-30648a6a-7fff-4585-c132-4ae3bd3b5fe1">
</b></p>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><b
style="font-weight:normal;"
id="docs-internal-guid-30648a6a-7fff-4585-c132-4ae3bd3b5fe1"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">This is a Call for Papers to the Journal of Artificial Intelligence Research (JAIR) Special Track on the topic of Multi-Agent Path Finding (</span><a
href="https://jair.org/index.php/jair/SpecialTrack-MAPF"
style="text-decoration:none;" moz-do-not-send="true"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#1155cc;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">https://jair.org/index.php/jair/SpecialTrack-MAPF</span></a><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">).</span></b></p>
<b style="font-weight:normal;"
id="docs-internal-guid-30648a6a-7fff-4585-c132-4ae3bd3b5fe1"> <br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">TRACK EDITORS:</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Daniel Harabor, Monash University</span></p>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Sven Koenig, University of California, Irvine</span></p>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Jingjin Yu, Rutgers University</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">TRACK OVERVIEW:</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Multi-Agent Path Finding (MAPF) is the abstract combinatorial problem of computing collision-free movement plans for a team of cooperative agents. The ability to solve instances of MAPF, efficiently and effectively, is a key enabler for many current and emerging industrial applications. These include warehouse logistics, train planning, pipe routing, robotic manufacturing, and many others.</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">MAPF is studied by researchers and practitioners from across all areas of Artificial Intelligence, including Planning, Discrete Optimisation, Heuristic Search, Machine Learning, and Robotics. Topics of interest include but are not limited to:</span></p>
<br>
<ul
style="margin-top:0;margin-bottom:0;padding-inline-start:48px;">
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Theoretical foundations and complexity analyses.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Symbolic approaches for solving MAPF, including search algorithms, compilation and reduction methods as well as reactive and rule-based techniques.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Learning approaches for solving MAPF, including supervised, unsupervised, and reinforcement techniques.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Generalisations of MAPF, including agent kino-dynamics, limited communication, and delivery deadlines.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Lifelong MAPF, including online planning, task allocation, execution monitoring, and explainability.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Execution considerations, including action failures, agent delays, dynamic map changes, and other sources of uncertainty.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Thoughtful critiques, meta-analyses, and surveys of the subject area.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Empirical analyses and MAPF benchmarks.</span></p></li>
<li dir="ltr"
style="list-style-type:disc;font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;"
aria-level="1"><p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"
role="presentation"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Real-world applications.</span></p></li>
</ul>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">CALL FOR SUBMISSIONS:</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">We invite researchers and practitioners to submit novel, original, and significant works, on all aspects of MAPF, to the JAIR special track.</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Submissions must be original, meaning that they have not previously appeared in the archival proceedings of any scholarly conference or journal. Papers that have only appeared at workshops or only as extended abstracts of no more than 2 pages are considered original. Substantially extended and improved versions of archival conference papers may also be considered original, provided that authors include appropriate citations to the conference paper and explain how their new submission extends and improves upon the earlier work.</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Novelty and significance can be established by the artificial intelligence techniques themselves, their analysis, their experimental evaluations (including via comparisons to existing techniques), and by their application to important industrial settings. Novelty and significance can also be demonstrated via thoughtful critiques of the area. Surveys and meta-analyses in particular should enrich the body of scholarly work being discussed.</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">SUBMISSION INFORMATION:</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">The submission period is July 1, 2024 to December 31, 2024. </span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Instructions for authors are available from the journal website: </span><a
href="https://jair.org/index.php/jair/about/submissions"
style="text-decoration:none;" moz-do-not-send="true"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#1155cc;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:underline;-webkit-text-decoration-skip:none;text-decoration-skip-ink:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">https://jair.org/index.php/jair/about/submissions</span></a></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Our target response time for accept/reject decisions is 3 months from the time of submission. Some articles may require revision and re-reviewing before a final decision is made.</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">Articles included in the special track will be made available as soon as they have been accepted.</span></p>
<br>
<p dir="ltr"
style="line-height:1.38;margin-top:0pt;margin-bottom:0pt;"><span
style="font-size:11pt;font-family:Arial,sans-serif;color:#000000;background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">We look forward to receiving your submissions!</span></p>
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