{"id":18,"date":"2020-01-02T14:26:17","date_gmt":"2020-01-02T14:26:17","guid":{"rendered":"https:\/\/scitope.com\/control20\/?page_id=18"},"modified":"2025-05-23T09:00:15","modified_gmt":"2025-05-23T09:00:15","slug":"program","status":"publish","type":"page","link":"https:\/\/scitope.com\/control\/?page_id=18","title":{"rendered":"Special Tracks"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]<\/p>\n

Track: AI NEXT & AI Transformation<\/strong><\/h5>\n
Track Organizers:
\n<\/strong>P\u00e9ter Baranyi<\/h6>\n

Scope:
\nThe special track is dedicated to emerging paradigms in AI science, with a particular emphasis on areas such as AI optimization, and the enhancement of precision, explainability, and provability in AI systems. It seeks to advance fundamental mathematical frameworks that offer provable performance guarantees for AI-driven control solutions\u2014surpassing conventional, experience-based and heuristic learning methods. In the regards of Explainable AI, the track specifically welcomes contributions aimed at developing linguistic interpreters of AI \u201cthinking,\u201d to make the reasoning and decision-making processes of AI systems more transparent and intelligible.[\/vc_column_text][vc_column_text]<\/p>\n

Track: Data-Driven Polytopic Modeling and Control Theories<\/strong><\/h5>\n
Track Organizers:
\n<\/strong>Imre Kocsis, Attila Gil\u00e1nyi<\/h6>\n

Scope:
\nThe purpose of the special track is three-fold, and accordingly, it basically announces three sections. One on theoretical background and one each on engineering and psychological applications as follows.[\/vc_column_text][vc_column_text]<\/p>\n

Session: Engineering Applications<\/strong><\/h5>\n
Track Organizers:
\n<\/strong>Husam A. Neamah, S\u00e1ndor Hajdu<\/h6>\n
Scope:<\/h6>\n

This Session is application-oriented and aims to introduce tensor product-based polytopic modelling and control in engineering areas that have not been attempted before.
\nTopics include tensor product-based:
\n\uf0b7 control of LPV systems
\n\uf0b7 disturbance observers
\n\uf0b7 condition monitoring of engineering systems
\n\uf0b7 electrical energy production
\n\uf0b7 energy distribution (power electronics network pollution)
\n\uf0b7 environmental effects (noise and other environmental pollution) modeling[\/vc_column_text][vc_column_text]<\/p>\n

Session: Theoretical Concepts<\/strong><\/h5>\n
Track Organizers:
\n<\/strong>Imre Kocsis, Attila Gil\u00e1nyi<\/h6>\n
Scope:<\/h6>\n

Papers dealing with the theoretical background of tensor product based polytopic modeling are invited.
\nTopics include
\n\uf0b7 Characterization of problems that can be successfully modeled using the tensor product method. Discussion of applicability.
\n\uf0b7 Characterization of the potential results provided by the application of the tensor product method, comparison with other modeling techniques.
\n\uf0b7 Problem-specific issues in the application of the tensor product method in various fields.
\n\uf0b7 Enforcement of model-related expectations, manipulation of vertices („convex hull”), special transformations.
\n\uf0b7 Application of tensor product-based models.[\/vc_column_text][vc_column_text]<\/p>\n

Session: Cognitive Modeling<\/strong><\/h5>\n
Track Organizers:
\n<\/strong>Csilla Csukonyi, Anna Sud\u00e1r<\/h6>\n
Scope:<\/h6>\n

The Session goes beyond the scope of engineering modelling and expectations, papers that translate verbal psychological and emotional models established on a statistical basis into tensor product-based polytopic form.
\nTopics include tensor product-based modeling of:
\n\uf0b7 sports persistence
\n\uf0b7 human robot interaction
\n\uf0b7 virtual reality aspects[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"

[vc_row][vc_column][vc_column_text] Track: AI NEXT & AI Transformation Track Organizers: P\u00e9ter Baranyi Scope: The special track is dedicated to emerging paradigms in AI science, with a particular emphasis on areas such as AI optimization, and the enhancement of precision, explainability, and provability in AI systems. It seeks to advance fundamental mathematical frameworks that offer provable performance […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"class_list":["post-18","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/scitope.com\/control\/index.php?rest_route=\/wp\/v2\/pages\/18","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scitope.com\/control\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/scitope.com\/control\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/scitope.com\/control\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/scitope.com\/control\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=18"}],"version-history":[{"count":11,"href":"https:\/\/scitope.com\/control\/index.php?rest_route=\/wp\/v2\/pages\/18\/revisions"}],"predecessor-version":[{"id":190,"href":"https:\/\/scitope.com\/control\/index.php?rest_route=\/wp\/v2\/pages\/18\/revisions\/190"}],"wp:attachment":[{"href":"https:\/\/scitope.com\/control\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=18"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}