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KI - Künstliche Intelligenz

KI - Künstliche Intelligenz

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

Editor-in-Chief: Daniel Sonntag

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

Journal no. 13218

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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.

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Reintegrating Artificial Intelligence and Robotics, Vol. 33, Issue 4

A major goal of Artificial Intelligence (AI) is to create autonomous, intelligent machines, or robots, that can sense their surroundings, reason about what they have perceived, plan their next actions, and act accordingly to accomplish their tasks. Moreover, robots should be able to learn from their own experience (including interactions with other agents) and adapt to changing conditions within their environments over their lifetime. Several of these challenges have been addressed and investigated by different subdisciplines of AI including Perception, Knowledge Representation & Reasoning, Planning, Interaction, and Learning. However, although these research areas have made tremendous progress over the last decade, their developed methods and techniques have not always been reintegrated into situated robot systems and deployed in the real world. It is the aim of this Special Issue on "Reintegrating Artificial Intelligence and Robotics" to emphasize that the reintegration of AI methods is a non-trivial factor in the design, development and evaluation of robot systems. In particular, we are interested in work related to both fully-integrated robots systems that use methods of AI to perform complex tasks in realistic environments and fundamental AI techniques that have the potential to transform the capabilities of robot systems, but which not been convincingly demonstrated in integrated systems.

Artificial Intelligence in Games, Vol. 34, Issue 1

The special issue focuses on artificial intelligence (AI) methods applied in and for different types of games (e.g., board games, video games, serious games). Games have been shown to be the perfect testbed for advanced AI methods. AI in games is now a well established research area with two dedicated conferences and as well as a dedicated journal. Especially deep learning methods have recently proven to beat the best human experts in Atari video games and the game Go. Other methods such as evolutionary computation have been shown to allow complete new types of games through procedural content generation. While there has been much progress in game AI recently, some games such as StarCraft remain beyond even the most advanced AI algorithms. The goal of this special issue is to present a survey of the current research in Game AI and emerging trends in this area.

Challenges in Interactive Machine Learning, Vol. 34, Issue 2

Designing successful interactive learning schemes requires to solve a number of key challenges like minimizing the cognitive cost for the user while optimizing query informativeness, devising effective interaction protocols based on different types of queries (membership, ranking, search, explanation, etc.), producing optimal questions by explicitly and efficiently capturing the uncertainty of the model, distributing the load of query answering across multiple teachers with heterogeneous abilities, designing or estimating realistic models of user behavior, increasing tolerance to noise and actively guiding the user toward providing better and more robust supervision, and, more generally, automatically discovering the user's expertise level and adapting the interaction accordingly. Such an interaction is likely to help make such systems more transparent and the results more explainable. Only then interactive learning will unlock unprecedented opportunities for both scientific research and commercial exploitation in Artificial Intelligence, Health Care, Environment and Climate, Physics and Astronomy, Chemistry, Bioinformatics, Agriculture, Social Web, Finance, e-Commerce, and Design, among other domains. This special issue aims at surveying established research in interactive learning, as well as overviewing recent advances on algorithms, models and effective process design around humans in the loop.

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.

    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 the entire field of artificial intelligence. The journal presents 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, it will as well serve as a media of communication between the members of the division and the parent society.

    The journal is published in English.

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