AIAA 2022 Fall Symposium: Lessons Learned for Autonomous Assessment of Machine Abilities (LLAAMA)
------------ Symposium Date: November 17-19, 2022 Symposium Location: Arlington, Virginia, USA Submission Deadline: August 26, 2022 LLAAMA Symposium Webpage: https://cohrint.info/events/llaama-aaai22/ AIAA 2022 Fall Symposium Main Webpage: https://aaai.org/Symposia/Fall/fss22participation.php#fs05 ------------ Description ------------ Modern civilian and military systems have created a demand for sophisticated intelligent autonomous machines capable of operating in uncertain dynamic environments. Such systems are realizable thanks in large part to major advances in perception and decision-making techniques, which in turn have been propelled forward by modern machine learning tools. However, these newer forms of intelligent autonomy raise questions about when/how communication of the operational intent and assessments of actual vs. supposed capabilities of autonomous agents impact overall performance. This symposium session will examine possibilities for enabling intelligent autonomous systems to self-assess and communicate their ability to effectively execute assigned tasks, as well as reason about the overall limits of their competencies and maintain operability within those limits. The symposium will bring together researchers working in this burgeoning area of research to share lessons learned, identify major theoretical and practical challenges encountered so far, and potential avenues for future research and real-world applications. Topics ------------ We invite contributions from researchers in AI/expert systems, human factors, autonomous robotics and control/complex systems engineering, and other related disciplines that explore several key areas, including: * Applications and studies of competency self-assessments in field robotics and other real-world autonomous systems * Measures of competency for operational self-assessment by autonomous agents * AI/ML, uncertainty quantification, formal methods, and algorithmic meta-reasoning techniques to enable/support autonomous competency self-assessment * Presentation and communication of machine generated competency self-assessments to human users/stakeholders * Techniques for evaluating the quality of machine generated competency self-assessments (e.g. correctness, completeness, fidelity, reliability). Submissions ------------ Please submit one of the following types of submissions via the AAAI FSS-22 EasyChair site as a .pdf document by August 26, 2022. Please use the AAAI paper template available here. * Regular papers (6-8 pages + references) * Position papers (2-4 pages + references) * Summary of previously published papers (1-2 pages) Following review by and feedback from the symposium’s technical committee, authors of selected papers will be invited to give a short presentation for their contribution at the symposium. Organizing Committee ------------ Aastha Acharya, Nicholas Conlon, Nisar Ahmed (University of Colorado Boulder); Rebecca Russell, Michael Crystal (The Charles Stark Draper Labs); Brett Israelsen (Raytheon Technologies Research Center); Ufuk Topcu (University of Texas Austin); Zhe Xu (Arizona State University); Daniel Szafir (University of North Carolina) Contact: Aastha Acharya (aastha.acha...@colorado.edu)
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