Details
| Original language | English |
|---|---|
| Title of host publication | KI 2018 |
| Subtitle of host publication | Advances in Artificial Intelligence - 41st German Conference on AI, 2018, Proceedings |
| Editors | Anni-Yasmin Turhan, Frank Trollmann |
| Place of Publication | Cham |
| Publisher | Springer Verlag |
| Pages | 357-365 |
| Number of pages | 9 |
| ISBN (electronic) | 978-3-030-00111-7 |
| ISBN (print) | 9783030001100 |
| Publication status | Published - 2018 |
| Event | 41st German Conference on Artificial Intelligence, KI 2018 - Berlin, Germany Duration: 24 Sept 2018 → 28 Sept 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11117 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Current trends, like digital transformation and ubiquitous computing, yield in massive increase in available data and information. In artificial intelligence (AI) systems, capacity of knowledge bases is limited due to computational complexity of many inference algorithms. Consequently, continuously sampling information and unfiltered storing in knowledge bases does not seem to be a promising or even feasible strategy. In human evolution, learning and forgetting have evolved as advantageous strategies for coping with available information by adding new knowledge to and removing irrelevant information from the human memory. Learning has been adopted in AI systems in various algorithms and applications. Forgetting, however, especially intentional forgetting, has not been sufficiently considered, yet. Thus, the objective of this paper is to discuss intentional forgetting in the context of AI systems as a first step. Starting with the new priority research program on ‘Intentional Forgetting’ (DFG-SPP 1921), definitions and interpretations of intentional forgetting in AI systems from different perspectives (knowledge representation, cognition, ontologies, reasoning, machine learning, self-organization, and distributed AI) are presented and opportunities as well as challenges are derived.
Keywords
- Artificial intelligence systems, Capacity and efficiency of knowledge-based systems (Intentional)
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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KI 2018: Advances in Artificial Intelligence - 41st German Conference on AI, 2018, Proceedings. ed. / Anni-Yasmin Turhan; Frank Trollmann. Cham: Springer Verlag, 2018. p. 357-365 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11117 LNAI).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Intentional forgetting in artificial intelligence systems
T2 - 41st German Conference on Artificial Intelligence, KI 2018
AU - Timm, Ingo J.
AU - Staab, Steffen
AU - Siebers, Michael
AU - Schon, Claudia
AU - Schmid, Ute
AU - Sauerwald, Kai
AU - Reuter, Lukas
AU - Ragni, Marco
AU - Niederée, Claudia
AU - Maus, Heiko
AU - Kern-Isberner, Gabriele
AU - Jilek, Christian
AU - Friemann, Paulina
AU - Eiter, Thomas
AU - Dengel, Andreas
AU - Dames, Hannah
AU - Bock, Tanja
AU - Berndt, Jan Ole
AU - Beierle, Christoph
N1 - Funding information: Acknowledgments. The authors are indebted to the DFG for funding this The authors are indebted to the DFG for funding this research: Dare2Del (SCHM1239/10-1), EVOWIPE (STA572/15-1), FADE (BE 1700/9-1, KE1413/10-1, RA1934/5-1), Managed Forgetting (DE420/19-1, NI1760 1-1), and AdaptPro (TI548/5-1). We would also like to thank our project partners for their fruitful discussion: C. Antoni, T. Ellwart, M. Feuerbach, C. Frings, K. Göbel, P. Kügler, C. Niessen, Y. Runge, T. Tempel, A. Ulfert, S. Wartzack.
PY - 2018
Y1 - 2018
N2 - Current trends, like digital transformation and ubiquitous computing, yield in massive increase in available data and information. In artificial intelligence (AI) systems, capacity of knowledge bases is limited due to computational complexity of many inference algorithms. Consequently, continuously sampling information and unfiltered storing in knowledge bases does not seem to be a promising or even feasible strategy. In human evolution, learning and forgetting have evolved as advantageous strategies for coping with available information by adding new knowledge to and removing irrelevant information from the human memory. Learning has been adopted in AI systems in various algorithms and applications. Forgetting, however, especially intentional forgetting, has not been sufficiently considered, yet. Thus, the objective of this paper is to discuss intentional forgetting in the context of AI systems as a first step. Starting with the new priority research program on ‘Intentional Forgetting’ (DFG-SPP 1921), definitions and interpretations of intentional forgetting in AI systems from different perspectives (knowledge representation, cognition, ontologies, reasoning, machine learning, self-organization, and distributed AI) are presented and opportunities as well as challenges are derived.
AB - Current trends, like digital transformation and ubiquitous computing, yield in massive increase in available data and information. In artificial intelligence (AI) systems, capacity of knowledge bases is limited due to computational complexity of many inference algorithms. Consequently, continuously sampling information and unfiltered storing in knowledge bases does not seem to be a promising or even feasible strategy. In human evolution, learning and forgetting have evolved as advantageous strategies for coping with available information by adding new knowledge to and removing irrelevant information from the human memory. Learning has been adopted in AI systems in various algorithms and applications. Forgetting, however, especially intentional forgetting, has not been sufficiently considered, yet. Thus, the objective of this paper is to discuss intentional forgetting in the context of AI systems as a first step. Starting with the new priority research program on ‘Intentional Forgetting’ (DFG-SPP 1921), definitions and interpretations of intentional forgetting in AI systems from different perspectives (knowledge representation, cognition, ontologies, reasoning, machine learning, self-organization, and distributed AI) are presented and opportunities as well as challenges are derived.
KW - Artificial intelligence systems
KW - Capacity and efficiency of knowledge-based systems (Intentional)
UR - http://www.scopus.com/inward/record.url?scp=85054553593&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-00111-7_30
DO - 10.1007/978-3-030-00111-7_30
M3 - Conference contribution
AN - SCOPUS:85054553593
SN - 9783030001100
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 357
EP - 365
BT - KI 2018
A2 - Turhan, Anni-Yasmin
A2 - Trollmann, Frank
PB - Springer Verlag
CY - Cham
Y2 - 24 September 2018 through 28 September 2018
ER -