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Präsentation studentischer Arbeiten

MO, 18.5., 16-18 Uhr (Ergebnisse des Bachelor-Projekts Verteiltes Problemlösen) und DO, 21.5., 9-12 Uhr (Ergebnisse Studentischer Arbeiten zum Thema Induktion von Zahlenreihen)

Kolloquium Montag, 4.5.15

Fritz Wysotzki (TU Berlin): Modelle des Assoziativen Gedächtnisses

Vortragsankündigung 28.4.15

Karriereverläufe von Informatikerinnen und Informatikern nach der Familiengründungsphase


Ute Schmid hält Einführungsvortrag in Kognitive Systeme im Rahmen der Seminarreihe der GI Regionalgruppe Würzburg

13.4.15: Ute Schmid gives Webinar Talk on Inductive Programming

for the monthly Webinar of the NSF Project ExCAPE: Expeditions in Computer Augmented Program Engineering, see:

Kolloquium Montag, 30.3.15,

Sebastian Boosz: Applying Anti-Unification Strategies to Matching and Generalization of Recursive Functions - Investigating a Second-order approach for Learning from Examples (Masterarbeit AI)

Kolloquium Dienstag, 24.3.15,

Frederic Ehmann: Künstliche Intelligenz in Computerspielen -- Lernen von Handlungsstrategien eines autonomen Agenten am Beispiel eines Jump 'n' Run Computerspiels (Masterarbeit AI)

February 02, 2015

Experimentierkasten Informatik gewinnt Preis


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Short portrait Cognitive Systems 

In the research domain Cognitive Systems (CogSys) we are concerned with the development of approaches, concepts, and methods for design, description, construction and analysis of intelligent systems based on cognitive principles. Our research strategy is to combine empirical studies of cognitive phenomena, development of algorithms, and their testing in different areas of application. Main topics of our group are induction and learning as well as planning and problem solving in single- and multi-agent settings. Especially, we are interested in the inductive synthesis of recursive functional programs from incomplete specifications (e.g., input/output examples) which can be seen as a general approach to learning productive rules from experience. Furthermore, we investigate analogical reasoning as a powerful approach to problem solving as a special mechanism of knowledge acquisition. Application areas are, for example, support of human problem solvers in the domains of software development, classifier learning for medical diagnostics, quality control, decision support or incident mining and assistant systems for activities of daily life. 

Introductory slides and hand-out in German: [pdf slides] [pdf text]