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Computer Science - Artificial Intelligence | KI - Künstliche Intelligenz – incl. option to publish open access

KI - Künstliche Intelligenz

KI - Künstliche Intelligenz

German Journal on Artificial Intelligence - Organ des Fachbereichs "Künstliche Intelligenz" der Gesellschaft für Informatik e.V.

Managing editor: Klaus-Dieter Althoff

ISSN: 0933-1875 (print version)
ISSN: 1610-1987 (electronic version)

Journal no. 13218

OpenAccessGerman_jnls_July_2013

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.

Preview:

Space Robotics

While Space Exploration may be considered anything but dull, it certainly is very dangerous. Expanding our knowledge on the solar system to look for clues to such fundamental questions as the origins of life, or a sustained human presence on anything other than earth may well be worth the risk. The involved costs for mitigating the risk of human space flight are prohibitive. Robotic missions, like the hugely successful Mars Exploration Rovers, have shown that Robotics as a sub-field of Artificial Intelligence can perform scientific exploration activities without human presence, and will play an even more prominent role in future mission scenarios. World wide technology research efforts are continuesly expanded the capabilities of mobile robotic systems. This special issue on "Space Robotics" of the Künstliche Intelligenz Journal seeks to present a collection of research efforts, industry activities and other insights into this hugely interesting and versatile field of AI.

The topics of interest include, but are not limited to:

- Exploration systems and technologies
- Orbital servicing
- Human mission support
- Operations support
- System design/architecture/behavior

The Künstliche Intelligenz journal supports the following lists of formats: Technical contributions, research projects, discussions, dissertation abstracts, conference reports and book reviews. If you are interested in contributing to this special issue, please contact one of the guest editors:

Jakob Schwendner
Robotics Innovation Center
Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI)
28359 Bremen
jakob.schwendner@dfki.de

Prof. Frank Kirchner
Robotics Innovation Center
Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI)
28359 Bremen
frank.kirchner@dfki.de

Bernd Sommer
Deutschen Zentrums für Luft- und Raumfahrt (DLR)
Königswintererstrasse 522-524
53227 Bonn
bernd.Sommer@dlr.de

Multi-Agent Decision Making

Classical decision making is concerned with how rational agents make optimal decisions. In distributed decision making complex problems are divided into smaller ones and decisions are made in a distributed manner. Also, it often is the case that all involved decision makers are sharing— willingly or not—a global objective and that they are somewhat cooperative. In general, this is not the case for multi-agent decision making which is concerned with self-interested agents pursuing their own objectives. Those objectives may be consistent but can just as well be completely contradicting; they can be publicly known or private. As a consequence, good decisions no longer only depend on the respective agent’s capabilities and the characteristics of the environment, but to a great extent on how other agents behave and on the interaction with them. In most settings these behaviors influence each other and that complicates matters further—new tools and techniques are needed.

This special issue will focus on multi-agent decision making. Topics of interest include but are not limited to:

– Logics for multi-agent systems
– Game theory and (computational) social choice
– Foundations of multi-agent systems
– Multi-agent planning and control
– Norms and social laws
– Argumentation and negotiation
– Decision theory

Possible contribution formats are technical articles, reports of research projects, dissertation summaries, book reviews, and conference reports. If you are interested in contributing to this special issue please contact the guest editor as soon as possible:

Dr. Nils Bulling
Department of Informatics
Clausthal University of Technology
Julius-Albert-Str. 4
38678 Clausthal-Zellerfeld, Germany
bulling@in.tu-clausthal.de

Re-integrating AI

Researchers in AI and Robotics have in common the desire to ‘make robots intelligent’, evidence of which can be traced back to the earliest AI systems. One major contribution of AI to Robotics is the model-centered approach, whereby intelligence is the result of reasoning in models of the world which can be changed to suit different environments, physical capabilities, and tasks. Dually, robots have contributed to the formulation and resolution of challenging issues in AI, and are constantly eroding the unrealistic modeling abstractions underlying AI problem solving techniques. Fortyeight years after the first AI-driven robot, this special issue on ‘Reintegrating AI’ seeks to provide a fresh and up-to-date look at the opportunities, challenges and successes which lie at the intersection of AI and Robotics. Topics of interest include, but are not limited to:

– Integration of Path and Motion Planning with Task Planning
– Knowledge Representation and Reasoning for robots
– Qualitative representations for robots
– Semantic mapping and reasoning with semantic maps
– Hybrid continuous/discrete reasoning
– Constraint-based reasoning for robots
– Continuous planning and on-line problem solving for robots
– System-level AI for robots
– Knowledge acquisition and knowledge exchange between robots
– Reasoning with uncertain and inconsistent knowledge
– Experience-based learning for robots
– High-level reasoning for exploration

The Künstliche Intelligenz Journal, which is published and indexed by Springer, supports the following lists of formats: Technical contributions, research projects, discussions, dissertation abstracts, conference reports and book reviews. Interested authors should contact the guest editors as soon as possible:

Dr. Federico Pecora
Center for Applied Autonomous Sensor Systems
Örebro University
70182 Örebro, Sweden
federico.pecora@oru.se

Prof. Achim J. Lilienthal
Center for Applied Autonomous Sensor Systems
Örebro University
70182 Örebro, Sweden
achim.lilienthal@oru.se

Related subjects » Artificial Intelligence - Software Engineering

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    Artificial Intelligence has successfully established itself as a scientific discipline in research and education and has become an integral part of Computer Science with an interdisciplinary character. AI deals with both the development of information processing systems that deliver “intelligent” services and with the modeling of human cognitive skills with the help of information processing systems. Research, development and applications in the field of AI pursue the general goal of creating processes for taking in and processing information that more closely resemble human problem-solving behavior, and to subsequently use those processes to derive methods that enhance and qualitatively improve conventional information processing systems.

    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 that are implemented using AI methods – and thus provides readers with the latest developments in and well-founded background information on all relevant aspects of artificial intelligence. A highly reputed team of editors from both university and industry will ensure the scientific quality of the articles.

    The journal provides all members of the AI community with quick access to current topics in the field, while also promoting vital interdisciplinary interchange.

    The journal is published in English; articles in German are also accepted

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