<div dir="ltr"><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="font-style:inherit;font-variant:inherit;font-stretch:inherit;font-size:inherit;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;border:0px;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"><br class="gmail-Apple-interchange-newline"><b>Title</b></span><span style="font:inherit;border:0px;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">: </span><span style="font-style:inherit;font-variant:inherit;font-stretch:inherit;font-size:inherit;line-height:inherit;font-family:inherit;font-kerning:inherit;font-feature-settings:inherit;border:0px;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">AAAI</span><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> Symposium on Human-Like Learning</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Description:</span></b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> Recent machine-learning research has made incredible progress across a wide range of tasks. While many systems can achieve human-like performance, one area that is currently under explored is how to realize <b>human-like learning</b> capabilities within these systems. For example, machine learning typically employs batch training and requires more data and computation than people to achieve similar capabilities. The resulting models are effective, but difficult to update in the face of new data without costly retraining. In contrast, humans excel at rapidly assimilating new information on the fly from a limited number of examples. More research is needed to investigate human-like capabilities, such as efficient, incremental learning, and to explore the design of artificial systems that can also exhibit them.</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">General Themes:</span></b></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Identification of key characteristics of human-like learning to target in AI/ML research, and what makes them challenging for current approaches;</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Ongoing and proposed research into how to create artificial systems that exhibit human-like learning;</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Approaches for evaluating such systems; and</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Exploration of the broader context and impacts of this research, such as how human-like learning systems might complement/benefit current machine learning systems and humanity.</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Relevant Topics (not exhaustive):</span></b></p><ul type="disc" style="color:rgb(36,36,36);font-size:15px;margin-top:0px;margin-bottom:0px"><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Cognitive architectures</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Interactive task learning</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Extended/continual learning</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Probabilistic programming</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Concept formation</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Analogical and case-based learning</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Logic-based learning</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Simulated students</li><li style="color:rgb(33,33,33);font-size:11pt;font-family:Calibri,sans-serif;margin:0px">Human-like neural network learning</li></ul><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Format:</span></b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> The symposium will consist of a small number of invited speakers, followed by approximately 20 technical presentations and a poster session. Each talk will be allotted 30-minutes (20 for talk and 10 for discussion). There will also be coffee breaks and time for broader reflections and discussions.</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Submission: </span></b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Authors will submit abstracts, which the organizing committee will use to decide on session topics and presentations. Speaker abstracts will also be shared with attendees. Authors of submissions that are not presented as talks will be invited to participate in a poster session during the first day. In choosing presenters, the committee will give preference to submissions that are more closely aligned to the overarching theme, while also trying to give coverage to different aspects of the theme.</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Please format abstracts using the AAAI Author Kit (<a href="https://aaai.org/authorkit24-2/" target="_blank" rel="noopener noreferrer" title="https://aaai.org/authorkit24-2/" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">https://aaai.org/authorkit24-2/</span></a>) and submit via easychair (<a href="https://easychair.org/my/conference?conf=sss24" target="_blank" rel="noopener noreferrer" title="https://easychair.org/my/conference?conf=sss24" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">https://easychair.org/my/conference?conf=sss24</span></a>).</span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">Organizing Committee:</span></b></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Christopher J. MacLellan, Georgia Institute of Technology, <a href="mailto:cmaclell@gatech.edu" title="mailto:cmaclell@gatech.edu" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">cmaclell@gatech.edu</span></a> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Ute Schmid, University of Bamberg, <a href="mailto:ute.schmid@uni-bamberg.de" title="mailto:ute.schmid@uni-bamberg.de" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">ute.schmid@uni-bamberg.de</span></a> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Douglas Fisher, Vanderbilt University, <a href="mailto:douglas.h.fisher@vanderbilt.edu" title="mailto:douglas.h.fisher@vanderbilt.edu" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">douglas.h.fisher@vanderbilt.edu</span></a> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">- Randolph M. Jones, Soar Technology, LLC, <a href="mailto:rjones@soartech.com" title="mailto:rjones@soartech.com" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">rjones@soartech.com</span></a> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> </span></p><p style="color:rgb(36,36,36);font-size:11pt;font-family:Calibri,sans-serif;margin:0px"><b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)">For more info:</span></b><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(33,33,33)"> <a href="https://humanlikelearning.com/aaai24-ss/" target="_blank" rel="noopener noreferrer" title="https://humanlikelearning.com/aaai24-ss/" style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline"><span style="border:0px;font:inherit;margin:0px;padding:0px;vertical-align:baseline;color:rgb(0,120,215)">https://humanlikelearning.com/aaai24-ss/</span></a></span></p></div>