<html xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=us-ascii">
<meta name="Generator" content="Microsoft Word 15 (filtered medium)">
<style><!--
/* Font Definitions */
@font-face
{font-family:"Cambria Math";
panose-1:2 4 5 3 5 4 6 3 2 4;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0in;
font-size:11.0pt;
font-family:"Calibri",sans-serif;}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:#0563C1;
text-decoration:underline;}
.MsoChpDefault
{mso-style-type:export-only;
font-size:10.0pt;
font-family:"Calibri",sans-serif;
mso-ligatures:none;}
@page WordSection1
{size:8.5in 11.0in;
margin:1.0in 1.0in 1.0in 1.0in;}
div.WordSection1
{page:WordSection1;}
--></style>
</head>
<body lang="EN-US" link="#0563C1" vlink="#954F72" style="word-wrap:break-word">
<div class="WordSection1">
<div>
<p class="MsoNormal" style="margin-bottom:12.0pt"><span style="font-size:12.0pt">Before the RLC 2024 main conference, workshops on a variety of current topics will be held on August 9th, 2024 in Amherst, Massachusetts. We invite researchers interested in chairing
a workshop to submit proposals. <br>
<br>
Goal of RLC Workshops:</span></p>
<p class="MsoNormal"><span style="font-size:12.0pt">Workshops provide an informal, cutting-edge venue for discussion of works in progress and future directions. Good workshops have helped to crystallize common problems, explicitly contrast competing frameworks,
and clarify essential questions for a subfield or application area. </span></p>
<p class="MsoNormal"><span style="font-size:12.0pt"> </span></p>
<p class="MsoNormal"><span style="font-size:12.0pt">Potential workshop topics include, but are not limited to, the following:<br>
-Reinforcement learning algorithms,<br>
-Theoretical foundations of reinforcement learning,<br>
-Reinforcement learning in low-resource settings,<br>
-Representation learning for reinforcement learning,<br>
-Robustness, safety, and fairness in reinforcement learning,<br>
-Exploration in reinforcement learning,<br>
-Human-in-the-loop reinforcement learning and RLHF,<br>
-Imitation learning and inverse reinforcement learning,<br>
-Uncertainty in reinforcement learning,<br>
-Applications of reinforcement learning: e.g., resource allocation, recommendation systems, robotics, healthcare, climate change, agriculture, pandemic response, etc,<br>
-Societal impacts and policy aspects of reinforcement learning deployment,<br>
-Any other topic relevant to an appreciable fraction of the RLC community.<br>
<br>
Submission Instructions: <a href="https://rl-conference.cc/call_for_workshops.html" target="_blank"><span style="color:#1A73E8;text-decoration:none">https://rl-conference.cc/call_for_workshops.html</span></a><br>
<br>
Workshop Application Deadline: 8 March 2024 (11:00 PM - Pacific Time)<br>
Workshop Acceptance Notification: 20 March 2024</span></p>
<p class="MsoNormal"><span style="font-size:12.0pt"> </span></p>
<p class="MsoNormal"><span style="font-size:12.0pt">Best,</span></p>
<p class="MsoNormal"><span style="font-size:12.0pt">The RLC 2024 Workshop Co-Chairs</span></p>
<p class="MsoNormal"><span style="font-size:12.0pt">Daniel Brown, University of Utah</span></p>
<p class="MsoNormal"><span style="font-size:12.0pt">Josiah Hanna, University of Wisconsin, Madison</span></p>
<p class="MsoNormal"><span style="font-size:12.0pt"> </span></p>
</div>
</div>
</body>
</html>