<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">Apologies for cross-posting <br><div><span style="font-family: -webkit-standard;"><br></span></div><div><b>News</b>: The submission deadline has been extended to the <span style="color: rgb(255, 0, 0);"><b>7th of June</b></span></div><div><br></div><div>-------------------------------------------------------------------------------<br></div><div>CALL FOR PAPERS</div><div>-------------------------------------------------------------------------------<br></div><div><div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><br></div><div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><br></div><div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">KR4HI-2023 is the second International Workshop on Knowledge Representation for Hybrid intelligence which will be co-located with the 2nd international conference on Hybrid-Human Artificial Intelligence (HHAI 2022). The workshop will be held in Design Offices Macherei on June 26th, 2023. <br><br>Submission deadline:June 7th,</div><div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">Event: June 26th, Munich, Germany <br><br>Submission link: <a href="https://easychair.org/conferences/?conf=kr4hi2023">https://easychair.org/conferences/?conf=kr4hi2023</a></div><div style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;">Website for the workshop: <a href="https://sites.google.com/view/kr4hi-2023/home">https://sites.google.com/view/kr4hi-2023/home</a><br><br><br><p dir="ltr" style="margin: 0px 0pt 12px 10pt; max-width: 650pt; line-height: 1.4; padding-bottom: 5pt;"><br></p><div>-------------------------------------------------------------------------------<br></div><div>SUBMISSION GUIDELINES</div><div>-------------------------------------------------------------------------------</div><div><br></div><div>Submission format: Submissions for contributing papers must be original (i.e., not submitted to any other venue) and are required to be in CEUR format (see <a href="http://ceur-ws.org/HOWTOSUBMIT.html" target="_blank">http://ceur-ws.org/HOWTOSUBMIT.html</a>) with 12 pages + references (incl. acknowledgements +supplementary material if necessary). Previously published articles or preliminary works can also be submitted in the form of extended abstracts (2 pages + references). </div><br><br><br><div><div>-------------------------------------------------------------------------------<br></div><div>AIMS AND SCOPE</div><div>-------------------------------------------------------------------------------</div><p dir="ltr" class="zfr3Q CDt4Ke" style="box-sizing: border-box; font-variant-ligatures: none; margin: 15px 0px 0px; outline: none; position: relative; color: rgb(33, 33, 33); font-family: "Open Sans", sans-serif; line-height: 1.75;"><span class="C9DxTc" style="box-sizing: border-box;">As artificial intelligence (AI) technologies are playing more important roles in our daily lives than ever before, designing intelligent systems which can work with humans effectively (instead of replacing them) is becoming a central research theme, giving rise to hybrid intelligence (HI). HI stands for combining human and machine intelligence as a team in various scenarios, aiming to benefit from the complementary powers of both components in solving problems.</span></p><p dir="ltr" class="zfr3Q CDt4Ke" style="box-sizing: border-box; font-variant-ligatures: none; margin: 15px 0px 0px; outline: none; position: relative; color: rgb(33, 33, 33); font-family: "Open Sans", sans-serif; line-height: 1.75;"><span class="C9DxTc" style="box-sizing: border-box;">Developing such systems requires fundamentally novel solutions to major research problems in AI: current AI systems outperform humans in many cognitive tasks e.g., in pattern recognition, playing video games, generating images or even code snippets, yet they fall short when it comes to tasks such as causal modelling, common sense reasoning, and behavioural human capabilities such as explaining its own decisions, adapting to different environments, adaptability to multiple contexts, collaborating with human agents, etc. A particular challenge in developing such systems is to work with human input (high-level symbolic constraints or behavioural data).</span><span class="C9DxTc" style="box-sizing: border-box;"><span class="Apple-tab-span" style="box-sizing: border-box; white-space: pre;"> </span></span><span class="C9DxTc" style="box-sizing: border-box;"><span class="Apple-tab-span" style="box-sizing: border-box; white-space: pre;"> </span></span></p><p dir="ltr" class="zfr3Q CDt4Ke" style="box-sizing: border-box; font-variant-ligatures: none; margin: 15px 0px 0px; outline: none; position: relative; color: rgb(33, 33, 33); font-family: "Open Sans", sans-serif; line-height: 1.75; padding-bottom: 0px;"><span class="C9DxTc" style="box-sizing: border-box;">Knowledge representation (KR) as a sub-discipline of AI, deals with representing background knowledge and reasoning with symbolic constraints. KR has a key potential for contributing to the development of HI systems, because it naturally brings human understanding and formal semantics (the understanding of machines) together. With this idea in mind, we welcome a wide array of works that use a KR formalism (or develop one) in an HI scenario. These works can range from purely theoretical to applied, or from purely symbolic to neural-symbolic ones, e.g., from “learning systems which take human demonstrations and symbolic constraints into account” to “explainable AI systems that generate symbolic explanations for humans” or can be in the context of socio-technical systems which hybrid intelligence naturally falls under.</span><span class="C9DxTc" style="box-sizing: border-box;"><span class="Apple-tab-span" style="box-sizing: border-box; white-space: pre;"> </span></span></p><div><br></div><div>-------------------------------------------------------------------------------<br></div><div>LIST OF TOPICS</div><div>-------------------------------------------------------------------------------</div><p dir="ltr" class="zfr3Q CDt4Ke" style="font-size: 16px; box-sizing: border-box; font-variant-ligatures: none; margin: 15px 0px 0px; outline: none; position: relative; color: rgb(33, 33, 33); font-family: "Open Sans", sans-serif; line-height: 1.75;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">The workshop has an interdisciplinary theme and welcomes any work from any discipline which uses a KR formalism in a HI scenario. The relevant themes to be used in a HI scenario include but are not limited to:</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Argumentation Frameworks</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Integrating Learning and Reasoning (Neuro-Symbolic systems, Statistical Relational Learning)</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Formal or Applied Ontologies (Knowledge Graphs, Description Logics)</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Causal Inference/Counterfactual Reasoning</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Constraint Programming</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Epistemic Logics and Theory of Mind</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Formal Concept Analysis</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Automated Reasoning, Robotics and Planning</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Non-monotonic Reasoning (Answer-set Programming, Datalog)</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Models of uncertainty (Probabilistic Graphical models, Probabilistic/Fuzzy Logics)</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Temporal logics (Single-agent / Multiagent Logics)</span><br style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;"><span style="caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px;">• Preferential/Contextual Reasoning</span></p><div>-------------------------------------------------------------------------------<br></div><div>PUBLICATION</div><div>-------------------------------------------------------------------------------</div>Accepted papers will be published in CEUR workshop proceedings. Selected papers will be further invited for (extended version) submission to a special issue of the journal AI Communications.</div><div><br></div><div><br></div><div><div>-------------------------------------------------------------------------------<br></div><div>KEYNOTE SPEAKERS</div><div>-------------------------------------------------------------------------------</div></div><div><br></div><div><div>• Thomas Bolander (Technical University of Denmark) - From Dynamic Epistemic Logic to Socially Intelligent Robots </div><div>• Max van Duijn (Leiden University) - Theory of Mind in Large Language Models</div></div><div><br></div><div><br></div><div><br>Organisers: <br>Erman Acar (ILLC, University of Amsterdam) <br>Ana Ozaki (University of Bergen)<br>Rafael Peñaloza (University of Milano-Bicocca)<br>Stefan Schlobach (Vrije Universiteit Amsterdam) <br>Atefeh Zafarghandi (CWI & Vrije Universiteit Amsterdam)<br><br></div><div><br></div><div>For any question, please contact Erman Acar via email: erman.acar at uva.nl</div></div></div><font color="#5856d6"><span style="caret-color: rgb(88, 86, 214);"><br></span></font><br>Erman (also on behalf of Ana, Rafael, Stefan and Atefeh)<br><font color="#5856d6"><span style="caret-color: rgb(88, 86, 214);"><br><br></span></font></div></body></html>