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Kolloquium Montag, 4.5.15

Fritz Wysotzki (TU Berlin): Modelle des Assoziativen Gedächtnisses
Ausführlich

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)
Ausführlich

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)
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16.12.14

Michael Siebers für den Preis für gute Lehre an der Fakultät nominiert


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Kolloquium Montag, 8.12.14

Florian Muth & Sebastian Ulschmid: Anwendung von Feature-Extraktionsmethoden und Klassifikationslernen zur Identifikation von Fahrzeugtypen (Ergebnisse des Master-Projekts)
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MAC Dienstag, 2.12.14

Ute Schmid, Applying Inductive Program Synthesis to Induction of Number Series - A Case Study with IGOR2
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15.10.14

Dagstuhl Seminar 15442 accepted

We are please that our topic "Approaches and Applications of Inductive Programming" (AAIP) got accepted as Dagstuhl seminar.
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Kolloquium Montag, 13.10.2014

Martina Milovec: Applying Inductive Programming to Solving Number Series Problems - Comparing Performance of IGOR with Humans
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Alle News

 

 

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]