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<div class="">ESSAI</div>
<div class="">24-28 July 2023</div>
<div class="">Ljubljana, Slovenia</div>
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<div class="">*CALL FOR COURSE PROPOSALS*</div>
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<div class="">The 1st European Summer School in Artificial Intelligence - ESSAI 2023 24-28 July, 2023 will take place at the University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia.</div>
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<div class=""><a href="https://essai.ijs.si" class="">https://essai.ijs.si</a></div>
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<div class="">IMPORTANT DATES:</div>
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<div class=""> 24 Jan 2023: Course Title submission deadline (mandatory)</div>
<div class=""> 31 Jan 2023: Final submission</div>
<div class=""> 28 Feb 2023: Notification</div>
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<div class="">The European Summer School in Artificial Intelligence (ESSAI) is a new annual summer school held under the auspices of the European Association for Artificial Intelligence (EurAI). The ambition of ESSAI is to become the central meeting place
for students and young researchers in Artificial Intelligence to discuss current research and share knowledge.</div>
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<div class="">ESSAI will provide an interdisciplinary setting in which courses are offered in all areas of Artificial Intelligence and also from wider scientific, historical, and philosophical perspectives. The format of ESSAI is analogous to the European Summer
School in Logic, Language and Information (ESSLLI) which has been running since 1989. Courses will consist of five 90 minute sessions, offered daily (Monday-Friday) in a single week, to allow students to develop in-depth knowledge of a topic.</div>
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<div class="">The first ESSAI will be held in Ljubljana, Slovenia in between the 24th and 28th of July 2023. ESSAI 2023 aims to attract around 400 participants from all parts of Europe, as well as from North and Latin America, and Asia. </div>
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<div class="">TOPICS AND FORMAT</div>
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<div class="">ESSAI aims to cover all subdisciplines of AI and the interactions between them. </div>
<div class="">Proposals for courses at ESSAI 2023 are invited in all areas of Artificial Intelligence, including but not limited to the following: </div>
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<div class="">* Agent-based and Multi-agent Systems (MAS)</div>
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<div class="">* Ethics, Legal Issues, Explainable and Trustworthy AI (XAI)</div>
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<div class="">* Knowledge Representation and Reasoning (KR)</div>
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<div class="">* Natural Language Processing (NLP)</div>
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<div class="">* Neuro-Symbolic Learning and Reasoning (NeSy)</div>
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<div class="">* Planning & Strategic Reasoning (PLAN)</div>
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<div class="">* Reinforcement Learning (RL)</div>
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<div class="">* Robotics (ROB) </div>
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<div class="">* Search & Optimization (SO)</div>
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<div class="">* Supervised and Unsupervised Learning (ML)</div>
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<div class="">* Vision (VIS)</div>
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<div class="">Each course will consist of five 90 minute lectures, offered daily (Monday-Friday) in a single week. </div>
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<div class="">While foundational courses will typically focus on one subarea of AI, introductory and advanced courses are encouraged to present a broader perspective on AI, and should be of interest beyond one specific area.</div>
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<div class="">CATEGORIES</div>
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<div class="">Each proposal should fall under one of the following categories.</div>
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<div class="">* FOUNDATIONAL COURSES *</div>
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<div class="">Foundational courses present the basics of a research area to students with no prior knowledge in that area. They should be at an elementary level, without prerequisites in the course's topic, though possibly assuming a level of general scientific
maturity in the relevant discipline. They should enable researchers from related disciplines to become comfortable with the fundamental concepts and techniques of the course topic, thereby contributing to the interdisciplinary nature of our research community.</div>
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<div class="">* INTRODUCTORY COURSES *</div>
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<div class="">Introductory courses are central to ESSAI's mission. They are intended to introduce a research field to students, young researchers, and other non-specialists, and to foster a sound understanding of its basic methods and techniques. Introductory
courses should enable researchers from related disciplines to become competent in the course topic. Introductory courses that are cross-disciplinary may presuppose general knowledge of the relevant disciplines.</div>
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<div class="">* ADVANCED COURSES *</div>
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<div class="">Advanced courses are targeted primarily at graduate students who wish to acquire an understanding of current research in a field of Artificial Intelligence.</div>
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<div class="">PROPOSAL GUIDELINES</div>
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<div class="">To be considered, course proposals should closely adhere to the following guidelines:</div>
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<div class="">Course proposals can be submitted by no more than two lecturers, and courses must be presented by lecturers who submitted the proposal. All lecturers must possess a PhD or equivalent degree by the submission deadline for course proposals.</div>
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<div class="">Course proposals should explicitly state the intended course category. Proposals for introductory courses should indicate the intended level, for example, as it relates to standard textbooks and monographs in the area. Proposals for advanced courses
should specify the prerequisites in detail.</div>
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<div class="">Proposals must be submitted in PDF format via:</div>
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<div class=""><a href="https://easychair.org/conferences/?conf=essai2023" class="">https://easychair.org/conferences/?conf=essai2023</a></div>
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<div class="">and include all of the following:</div>
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<div class="">a. Personal information for each proposer: Name, affiliation, contact address, email, homepage (optional)</div>
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<div class="">b. General proposal information: Title, category</div>
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<div class="">c. Information about the course content:</div>
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<div class=""> Abstract of up to 150 words</div>
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<div class=""> Motivation and description (up to two pages)</div>
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<div class=""> Tentative outline</div>
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<div class=""> Expected level and prerequisites</div>
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<div class=""> Appropriate references (e.g. textbooks, monographs, proceedings, surveys)</div>
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<div class="">d. Information about the proposer(s) and course:</div>
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<div class=""> Whether the course will appeal to students outside of the main discipline of the course</div>
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<div class=""> Proposer(s)’s experience of delivering courses in an intensive one-week interdisciplinary setting</div>
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<div class=""> Evidence that the proposer(s) is an excellent lecturer</div>
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<div class="">To keep participation fees to a minimum, all the instructional and organizational work of ESSAI is performed on a completely voluntary basis. However, the registration fees of organizers and instructors will be waived, and travel and accommodation
expenses will be reimbursed up to a level which will be communicated along with the proposal notification. ESSAI can only guarantee reimbursement for at most one course lecturer, and can not guarantee full reimbursement of travel costs for lecturers from outside
of Europe. The organizers of ESSAI would appreciate any help in reducing the School's expenses by seeking partial or complete coverage of travel and accommodation expenses from other sources.</div>
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<div class="">SUBMISSION INFORMATION</div>
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<div class="">By Jan 24, 2023:</div>
<div class="">Proposers must submit on EasyChair at least the name(s) of the lecturers(s), the ESSAI area+course level and a short abstract.</div>
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<div class="">By Jan 31, 2023:</div>
<div class="">Submission must be completed by uploading a PDF with the actual proposal as detailed above.</div>
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<div class="">SUBMISSION PORTAL</div>
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<div class="">Please submit your proposals to</div>
<div class=""><a href="https://easychair.org/conferences/?conf=essai2023" class="">https://easychair.org/conferences/?conf=essai2023</a></div>
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<div class="">ORGANIZING COMMITTEE</div>
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<div class="">Aleksander Sadikov (University of Ljubljana)</div>
<div class="">Vida Groznik (University of Primorska, University of Ljubljana) </div>
<div class="">Sašo Džeroski (Jožef Stefan Institute)</div>
<div class="">Jure Žabkar (University of Ljubljana)</div>
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<div class="">PROGRAM COMMITTEE</div>
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<div class="">Magdalena Ortiz (Umeå University), chair </div>
<div class="">Sašo Džeroski (Jožef Stefan Institute), local co-chair</div>
<div class="">Brian Logan (University of Aberdeen), associate chair </div>
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<div class="">Area chairs will be announced on the course website </div>
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<div class="">EurAI Board Representative </div>
<div class="">Giuseppe De Giacomo (Sapienza University of Rome)</div>
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<div>—</div>
<div>Magdalena Ortiz</div>
<div><font color="#a9a9a9" class="">(Maria Magdalena Ortiz de la Fuente)</font><br class="">
Associate Professor for Knowledge Representation and Reasoning</div>
<div>Department of Computing Science </div>
<div>Umeå University</div>
<div><a href="mailto:magdalena.ortiz@umu.se" class="">magdalena.ortiz@umu.se</a></div>
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