<html><head><meta http-equiv="Content-Type" content="text/html; charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div class="">========================</div><div class="">Call for Papers:</div><div class=""><br class=""></div><div class="">** Frontiers in AI: Advances in Goal, Plan and Activity Recognition **</div><div class=""><br class=""></div><div class="">Website: <a href="https://www.frontiersin.org/research-topics/16540/advances-in-goal-plan-and-activity-recognition" class="">https://www.frontiersin.org/research-topics/16540/advances-in-goal-plan-and-activity-recognition</a></div><div class="">========================</div><div class=""><br class=""></div><div class="">Goal and Plan recognition are two interdisciplinary problems that can be addressed using techniques from automated planning, natural language understanding, psychology, human-computer interfaces, machine learning, and more. However, many of these techniques cannot be trivially applied for goal and plan recognition. For example, when leveraging automated planning for goal recognition, additional information may be required for the recognition task, with respect to what is needed for compared to the planning task. This can include various limitations on the observations such as partialness and noise, correctness, partial domain model, and missing knowledge of an agent's preferences. As AI systems become more prevalent, new challenges arise to create accurate, explainable, and robust methods for goal and plan recognition algorithms in the real world.</div><div class=""><br class=""></div><div class="">Goal and plan recognition research have seen substantial recent research activity. Efforts include relaxing virtually some assumptions about the underlying recognition problems, dealing with domain models with imperfections and spurious observations, expanding recognition to continuous and stochastic domains, as well as those populated by multiple agents.</div><div class=""><br class=""></div><div class="">We are interested in original research and survey articles on the following, non-exhaustive list of topics:</div><div class="">- Goal/Plan recognition approaches using any type of domain model;</div><div class="">- Domain theory formalisms for goal and plan recognition;</div><div class="">- Learning domain models for goal and plan recognition;</div><div class="">- Recognition techniques to cope with domain imperfections (incomplete or faulty domain models, approximate domain models, and etc.);</div><div class="">- Integration of classical planning and learning for goal and plan recognition;</div><div class="">- Explainable goal and plan recognition;</div><div class="">- Applications of goal and plan recognition (services for helping the elderly people, identifying significant activities and places from GPS traces, parsing algorithms, Bayesian networks inference procedures and goal recognition for dialogue systems among others);</div><div class="">- Multiagent goal and plan recognition;</div><div class="">- Domain design for goal and plan recognition;</div><div class="">- Recognition of goals and plans of humans vs. virtual agents;</div><div class="">- Goal acquisition/elicitation for goal/plan recognition;</div><div class="">- Activity recognition in isolation or integrated with Goal and Plan Recognition;</div><div class=""><br class=""></div><div class="">========================</div><div class="">Topic Editors:</div><div class=""><br class=""></div><div class="">- Felipe Meneguzzi <<a href="mailto:felipe.meneguzzi@pucrs.br" class="">felipe.meneguzzi@pucrs.br</a>> (PUCRS, Brazil)</div><div class="">- Ramon Fraga Pereira <<a href="mailto:ramonfpereira@gmail.com" class="">ramonfpereira@gmail.com</a>> (Sapienza University of Rome, Italy)</div><div class="">- Reuth Mirsky <<a href="mailto:reuthde@gmail.com" class="">reuthde@gmail.com</a>> (University of Texas at Austin, United States)</div><div class="">- Mor Vered <<a href="mailto:mor.vered@monash.edu" class="">mor.vered@monash.edu</a>> (Monash University, Australia)</div><div class=""><br class=""></div><div class="">========================</div><div class="">Submission Deadlines:</div><div class=""><br class=""></div><div class="">- Abstract: 30 April 2021</div><div class="">- Manuscript: 30 April 2021</div><div class=""><br class=""></div><div class=""><b class="">Note that our Abstract deadline is a ** soft-one **, meaning that authors will be able to submit their Abstract until the manuscript deadline (30 April 2021). </b></div><div class=""> </div><div class=""><a href="https://www.frontiersin.org/research-topics/16540/advances-in-goal-plan-and-activity-recognition" class="">https://www.frontiersin.org/research-topics/16540/advances-in-goal-plan-and-activity-recognition</a></div><div class="">========================</div><div class=""><br class=""></div><div class="">If you have any questions, please do not hesitate to contact the topic editors.</div><div class="">
<span class="Apple-style-span" style="border-collapse: separate; font-variant-ligatures: normal; font-variant-east-asian: normal; font-variant-position: normal; line-height: normal; border-spacing: 0px; -webkit-text-decorations-in-effect: none;">--<br class="">Felipe Meneguzzi<br class=""><a href="mailto:felipe.meneguzzi@gmail.com" class="">felipe.meneguzzi@gmail.com</a></span>
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