KI - Künstliche Intelligenz

Permanent URI for this communityhttps://dl.gi.de/handle/20.500.12116/11025

The Scientific journal "KI – Künstliche Intelligenz" is the official journal of the division for artificial intelligence within the "Gesellschaft für Informatik e.V." (GI) – the German Informatics Society – with contributions from throughout the field of artificial intelligence. The journal presents all relevant aspects of artificial intelligence – the fundamentals and tools, their use and adaptation for scientific purposes, and applications which are implemented using AI methods – and thus provides the reader with the latest developments in and well-founded background information on all relevant aspects of artificial intelligence. For all members of the AI community the journal provides quick access to current topics in the field and promotes vital interdisciplinary interchange.

Authors with most Documents

Visser, Ubbo

Ragni, Marco

Richter, Kai-Florian

Sonntag, Daniel

Beetz, Michael

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1 - 20 of 801

1 Jahr KI bei Springer
(Springer, 2011) Schneeberger, Josef
14th International Semantic Web Conference 2015 Bethlehem, PA, USA; October 11–15
(Springer, 2016) Paulheim, Heiko
15 Years of Semantic Web: An Incomplete Survey
(Springer, 2016) Glimm, Birte; Stuckenschmidt, Heiner
It has been 15 years since the first publications proposed the use of ontologies as a basis for defining information semantics on the Web starting what today is known as the Semantic Web Research Community. This work undoubtedly had a significant influence on AI as a field and in particular the knowledge representation and Reasoning Community that quickly identified new challenges and opportunities in using Description Logics in a practical setting. In this survey article, we will try to give an overview of the developments the field has gone through in these 15 years. We will look at three different aspects: the evolution of Semantic Web Language Standards, the evolution of central topics in the Semantic Web Community and the evolution of the research methodology.
16 Years of RoboCup Rescue
(Springer, 2016) Sheh, Raymond; Schwertfeger, Sören; Visser, Arnoud
The RoboCup Rescue competitions have been initiated in 2000. To celebrate 16 years of research and development in this socially relevant initiative this article gives an overview of the experience gained during these competitions. This article provides an overview the state-of-the-art and the lessons learned from the RoboCup Rescue competitions.
20 Years of RoboCup
(Springer, 2016) Ferrein, Alexander; Steinbauer, Gerald
This summer, RoboCup competitions were held for the 20th time in Leipzig, Germany. It was the second time that RoboCup took place in Germany, 10 years after the 2006 RoboCup in Bremen. In this article, we give an overview on the latest developments of RoboCup and what happened in the different leagues over the last decade. With its 20th edition, RoboCup clearly is a success story and a role model for robotics competitions. From our personal view point, we acknowledge this by giving a retrospection about what makes RoboCup such a success.
20 Years of RoboCup
(Springer, 2016) Steinbauer, Gerald; Ferrein, Alexander
20 Years of RoboCup
(Springer, 2016) Visser, Ubbo
2018 IEEE Conference on Computational Intelligence and Games (CIG 2018)
(Springer, 2020) Winands, Mark H. M.
25 Jahre KI – ein persönlicher Rückblick
(Springer, 2011) Harms, Christine
3D-Roboterkartenbau in Osnabrück
(Springer, 2010) Hertzberg, Joachim; Lingemann, Kai; Lörken, Christopher; Nüchter, Andreas; Stiene, Stefan; Wiemann, Thomas
Seit Herbst 2004 existiert die Arbeitsgruppe „Wissensbasierte Systeme“ am Institut für Informatik der Universität Osnabrück. Ein Langfristziel der Arbeitsgruppe besteht darin, Schlussfolgerungs- und Planungsverfahren der KI für den Einsatz online und onboard auf mobilen Robotern einsetzbar zu machen. Ein daraus abgeleitetes Arbeitsthema ist der Bau von semantischen Roboterkarten basierend auf 3D-Laserscans bei 6-dimensionalen Scanposen. Wir geben einen Überblick über die wichtigsten Ergebnisse dazu und über unsere Perspektive dieses Themas für die Zukunft.
45 Jahre KI Zeitschrift?
(Springer, 2011) Bergmann, Ralph
A Brief Tutorial on How to Extract Information from User-Generated Content (UGC)
(Springer, 2013) Egger, Marc; Lang, André
In this brief tutorial, we provide an overview of investigating text-based user-generated content for information that is relevant in the corporate context. We structure the overall process along three stages: collection, analysis, and visualization. Corresponding to the stages we outline challenges and basic techniques to extract information of different levels of granularity.
A Camera-Based Mobility Aid for Visually Impaired People
(Springer, 2016) Schwarze, Tobias; Lauer, Martin; Schwaab, Manuel; Romanovas, Michailas; Böhm, Sandra; Jürgensohn, Thomas
We present a wearable assistance system for visually impaired persons that perceives the environment with a stereo camera system and communicates obstacles and other objects to the user in form of intuitive acoustic feedback. The system is designed to complement traditional assistance aids. We describe the core techniques of scene understanding, head tracking, and sonification and show in an experimental study that it enables users to walk in unknown urban terrain and to avoid obstacles safely.
A Cognitive Observer-Based Landmark-Preference Model
(Springer, 2017) Röser, Florian
A Combined Analytical and Search-Based Approach for the Inductive Synthesis of Functional Programs
(Springer, 2011) Kitzelmann, Emanuel
Inductive program synthesis addresses the problem of automatically generating (declarative) recursive programs from ambiguous specifications such as input/output examples. Potential applications range from software development to intelligent agents that learn in recursive domains. Current systems suffer from either strong restrictions regarding the form of inducible programs or from blind search in vast program spaces. The main contribution of my dissertation (Kitzelmann, Ph.D. thesis, 2010) is the algorithm Igor2 for the induction of functional programs. It is based on search in program spaces but derives candidate programs directly from examples, rather than using them as test cases, and thereby prunes many programs. Experiments show promising results.
A Differentiated Discussion About AI Education K-12
(Springer, 2021) Steinbauer, Gerald; Kandlhofer, Martin; Chklovski, Tara; Heintz, Fredrik; Koenig, Sven
AI Education for K-12 and in particular AI literacy gained huge interest recently due to the significantly influence in daily life, society, and economy. In this paper we discuss this topic of early AI education along four dimensions: (1) formal versus informal education, (2) cooperation of researchers in AI and education, (3) the level of education, and (4) concepts and tools.
A Double Take at Conferences: The Hybrid Format
(Springer, 2022) Turhan, Anni-Yasmin
A Framework for Learning Event Sequences and Explaining Detected Anomalies in a Smart Home Environment
(Springer, 2022) Baudisch, Justin; Richter, Birte; Jungeblut, Thorsten
This paper presents a framework for learning event sequences for anomaly detection in a smart home environment. It addresses environment conditions, device grouping, system performance and explainability of anomalies. Our method models user behavior as sequences of events, triggered by interaction of the home residents with the Internet of Things (IoT) devices. Based on a given set of recorded event sequences, the system can learn the habitual behavior of the residents. An anomaly is described as deviation from that normal behavior, previously learned by the system. One key feature of our framework is the explainability of detected anomalies, which is implemented through a simple rule analysis.
A Games Industry Perspective on Recent Game AI Developments
(Springer, 2020) Preuss, Mike; Risi, Sebastian
A GGP Feature Learning Algorithm
(Springer, 2011) Kirci, Mesut; Sturtevant, Nathan; Schaeffer, Jonathan
This paper presents a learning algorithm for two-player, alternating move GGP games. The Game Independent Feature Learning algorithm, GIFL, uses the differences in temporally-related states to learn patterns that are correlated with winning or losing a GGP game. These patterns are then used to inform the search. GIFL is simple, robust and improves the quality of play in the majority of games tested. GIFL has been successfully used in the GGP program Maligne.