DFG Project
Placeholder
Cognitive computing addresses problems characterized by ambiguity and uncertainty, meaning that it is used to handle problems humans are confronted with in everyday life. When developing a cognitive computing system which is supposed to act human-like one cannot rely on automated theorem proving techniques alone, since humans performing commonsense reasoning do not obey the rules of classical logics. This causes humans to be susceptible to logical fallacies, but on the other hand to draw useful conclusions automated reasoning systems are incapable of. Humans naturally reason in the presence of incomplete and inconsistent knowledge, are able to reason in the presence of norms as well as conflicting norms and are able to quickly reconsider their conclusions when being confronted with additional information. The versatility of human reasoning illustrates that any attempt to model the way humans perform commonsense reasoning has to use a combination of many different techniques. This project aims at the construction of a cognitive computing system by modeling aspects of human reasoning like emotions and human interactions. For this, we will extend classical logical reasoning with non-monotonic reasoning like defeasible logic and normative reasoning and combine it with machine learning techniques. This will not only be carried out on a theoretical level. Different components important to model the commonsense reasoning process will be developed and combined to a cognitive computing system which will be tested using benchmarks from commonsense reasoning.
Prof. Dr. Frieder Stolzenburg
Project leader
Hochschule Harz
Fachbereich Automatisierung und Informatik
Tel.: +49 (0) 39 43 / 659 333
Fax: +49 (0) 39 43 / 659 333
E-mail: fstolzenburg@hs-harz.de
Sophie Siebert
Hochschule Harz
Fachbereich Automatisierung und Informatik
Tel.: +49 (0) 39 43 / 659 391
E-mail: ssiebert@hs-harz.de
Prof. Dr. Ulrich Furbach
Project leader
Universität Koblenz-Landau
Fachbereich 4: Informatik
Tel.: +49 (0) 261 / 287 2728
E-mail: uli@uni-koblenz.de
Dr. Claudia Schon
Project leader
Universität Koblenz-Landau
Fachbereich 4: Informatik
Tel.: +49 (0) 261 / 287 2773
E-mail: schon@uni-koblenz.de
The DFG is the self-governing organisation for science and research in Germany. It serves all branches of science and the humanities. In organisational terms, the DFG is an association under private law. Its membership consists of German research universities, non-university research institutions, scientific associations and the Academies of Science and the Humanities.
Harz University of Applied Sciences. Meet an innovative university with state-of-the-art, market-aligned degree programmes, dedicated teaching staff in step with actual practice, helpful fellow students and first-class technical equipment. Students and teaching staff alike use our wireless LAN campus, the modern language and media centre, the library, the large AudiMax lecture hall as well as superbly equipped laboratories, where practically oriented teaching and research takes place.
The University of Koblenz-Landau is a young, medium-sized university. In 1990 the university emerged from the former teacher training college. In the meantime research and teaching are organised in three linked interdisciplinary subject areas entitled "Learning", "Society" and "Environment".
Claudia Schon.
Selection strategies for commonsense knowledge.
ArXiv Report abs/2202.09163, Cornell University Library, 2022. Submitted.
[http]
Claudia Schon, Ulrich Furbach, and Marco Ragni.
Modeling associative reasoning processes.
ArXiv Report abs/2201.00716, Cornell University Library, 2022.
[http]
Claudia Schon, Sophie Siebert, and Frieder Stolzenburg.
Negation in cognitive reasoning.
In Stefan Edelkamp, Ralf Möller, and Elmar Rueckert, editors, KI 2021: Advances in Artificial Intelligence - 44th German Conference on AI, 2021, Proceedings, volume
12873 of Lecture Notes in Computer Science, pages 217–232. Springer, 2021.
[http]
Ulrike Barthelmeß and Ulrich Furbach.
Consciousness: Just another technique?
KI, 35(3):441–444, 2021.
[http]
Christoph Beierle, Marco Ragni, Frieder Stolzenburg, and Matthias Thimm, editors.
Proceedings of FCR-2021 – 7th Workshop on Formal and Cognitive Reasoning, CEUR Workshop Proceedings 2961, 2021.
[http]
Ulrike Barthelmeß and Ulrich Furbach.
Künstliche intelligenz, quo vadis?
In Ulrich Beuttler et al., editors, Superintelligenz? Möglichkeiten und Grenzen
Künstlicher Intelligenz in interdisziplinärer Perspektive, volume 33 of Jahrbuch
der Karl-Heim Gesellschaft. Peter Lang, 2021.
[http]
Aravindan Chandrabose, Ulrich Furbach, Ashish Ghosh, et al.
Computational Intelligence in Data Science: Third IFIP TC 12 International
Conference, ICCIDS 2020, Chennai, India.
Revised Selected Papers, volume 578 of IFIP AICT. Springer Nature, 2020.
[http]
Christoph Beierle, Marco Ragni, Frieder Stolzenburg, and Matthias Thimm, editors.
Proceedings of the 6th Workshop on Formal and Cognitive Reasoning (FCR-2020).
CEUR Workshop Proceedings 2680, Bamberg, 2020.
[http]
Tjitze Rienstra, Claudia Schon, Steffen Staab.
Concept contraction in the description logic EL.
Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning. Vol. 17. No. 1. 2020. [http]
Christoph Beierle, Marco Ragni, Frieder Stolzenburg, and Matthias Thimm, editors.
Proceedings of the KI 2019 Workshop on Formal and Cognitive Reasoning – 8th Workshop on Dynamics of Knowledge and Belief (DKB-2019) and 7th Workshop KI & Kognition (KIK-2019), CEUR Workshop Proceedings 2445, Kassel, 2019 [http]
Ulrich Furbach, Teresa Krämer, and Claudia Schon.
Names are not just sound and smoke: Word embeddings for axiom selection.
In Pascal Fontaine, editor, Automated Deduction – CADE 27 – 27th International Conference on Automated Deduction, Natal, Brazil, August 27-30, 2019, Proceedings, volume 11716 of Lecture Notes in Computer Science, pages 250–268. Springer, 2019 [http]
Sophie Siebert, Claudia Schon, and Frieder Stolzenburg.
Commonsense reasoning using theorem proving and machine learning.
In Andreas Holzinger, Peter Kieseberg, A Min Tjoa, and Edgar Weippl, editors, Machine Learning and Knowledge Extraction – 3rd IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, LNCS 11713, pages 395–413, Canterbury, UK, 2019. Springer Nature Switzerland.
[http]
Ulrike Barthelmeß and Ulrich Furbach.
Künstliche Intelligenz aus ungewohnten Perspektiven: Ein Rundgang mit Bergson, Proust und Nabokov.
Springer, 2019.
[http]
Ulrich Furbach, Steffen Hölldobler, Marco Ragni, and Frieder Stolzenburg.
Cognitive reasoning. KI, 33(3), 2019. Edited special issue. [http]
Claudia Schon, Sophie Siebert, and Frieder Stolzenburg.
The CoRg project: Cognitive reasoning. KI, 33(3):293–299, 2019. [http]
Ulrich Furbach, Steffen Hölldobler, Marco Ragni, Claudia Schon, and Frieder Stolzenburg.
Cognitive reasoning: A personal view. KI, 33(3):209–217, 2019.
[http]
Sophie Siebert and Frieder Stolzenburg.
CoRg: Commonsense reasoning using a theorem prover and machine learning.
In Christoph Benzmüller, Xavier Parent, and Alexander Steen, editors, Selected Student Contributions and Workshop Papers of LuxLogAI 2018, volume 10 of Kalpa Publications in Computing, pages 20–26. EasyChair, 2019. Deduktionstreffen 2018, Luxembourg.
[http]
Christoph Beierle, Gabriele Kern-Isberner, Marco Ragni, Frieder Stolzenburg, and Matthias Thimm, editors.
Proceedings of the KI 2018 Workshop on Formal and Cognitive Reasoning.
7th Workshop on Dynamics of Knowledge and Belief (DKB-2018) and 6th Workshop KI & Kognition (KIK-2018), CEUR Workshop Proceedings 2194, Berlin, 2018. [http]
Ulrich Furbach, Claudia Schon.
Reasoning and Consciousness. Teaching a Theorem Prover to let its Mind Wander.
AITP 2018 – Proc. of 3rd Conference on Articial Intelligence and Theorem Proving. Abstracts.
[http]
Frieder Stolzenburg, Sandra Litz, Olivia Michael, and Oliver Obst.
The power of linear recurrent neural networks.
ArXiv Report abs/1802.03308, Cornell University Library, 2018. Latest revision 2022.
[http]
Ulrich Furbach:
AI – Artificial Imperfection.
Artificial Imperfection – with Paola Antonelli | R&D Salon 24 | The Museum of Modern Art | 03.04.2018. Video.
[http]
The predecessor project RatioLog aims at establishing a common model for deduction and behavior. To this end logical deduction and modeling continuous systems are to be combined, based on preceding work on non-monotonous calculi and hybrid automata. Deduction in classical logic is to be extended with several non-monotonous aspects, for example abduction or refutable argumentation. The extensions will not only be made on a theoretical level, but will also be implemented into the automated theorem prover E-KR-Hyper. LogAnswer, an open-domain question answering system that uses E-KRHyper and Wikipedia to answer natural-language questions (in German), will be expanded to a rational question answering system, providing an excellent testing field for evaluating the rational deduction.
German Blog Article: "Künstliche Intelligenz: Wo bleibt die Logik?"
https://www.hs-harz.de/blog/ki-forschung-wo-bleibt-die-logik
Workshop on KI & Kognition 2020:
http://www.fernuni-hagen.de/wbs/fcr2020
Workshop on KI & Kognition 2019:
http://www.fernuni-hagen.de/wbs/dkbkik2019
Workshop on Bridging the Gap between Human and Automated Reasoning:
http://ratiolog.uni-koblenz.de/bridging2019.html
Künstliche Intelligenz Journal - Special Issue on "Cognitive Reasoning" - Call for Papers
http://corg.hs-harz.de/KIJCall.html