This book constitutes the thoroughly refereed proceedings of the 30th Annual German Conference on Artificial Intelligence, KI 2007, held in Osnabrück, Germany, September 2007. The papers are organized in topical sections on cognition and emotion, semantic Web, analogy, natural language, reasoning, ontologies, spatio-temporal reasoning, machine learning, spatial reasoning, robot learning, classical AI problems, and agents.
This book constitutes the refereed proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020, held in Bamberg, Germany, in September 2020. The 16 full and 12 short papers presented together with 6 extended abstracts in this volume were carefully reviewed and selected from 62 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research. KI 2020 had a special focus on human-centered AI with highlights on AI and education and explainable machine learning. Due to the Corona pandemic KI 2020 was held as a virtual event.
This book constitutes the thoroughly refereed proceedings of the 32nd Annual German Conference on Artificial Intelligence, KI 2009, held in Paderborn, Germany, in September 2009. The 76 revised full papers presented together with 15 posters were carefully reviewed and selected from 126 submissions. The papers are divided in topical sections on planning and scheduling; vision and perception; machine learning and data mining; evolutionary computing; natural language processing; knowledge representation and reasoning; cognition; history and philosophical foundations; AI and engineering; automated reasoning; spatial and temporal reasoning; agents and intelligent virtual environments; experience adn knowledge management; and robotics.
The 33rd Annual German Conference on Arti?cial Intelligence (KI 2010) took place at the Karlsruhe Institute of Technology KIT, September 21–24, 2010, under the motto “Anthropomatic Systems.” In this volume you will ?nd the keynote paper and 49 papers of oral and poster presentations. The papers were selected from 73 submissions, resulting in an acceptance rate of 67%. As usual at the KI conferences, two entire days were allocated for targeted workshops—seventhis year—andone tutorial. The workshopand tutorialma- rials are not contained in this volume, but the conference website, www.ki2010.kit.edu,will provide information and references to their contents. Recent trends in AI research have been focusing on anthropomatic systems, which address synergies between humans and intelligent machines. This trend is emphasized through the topics of the overall conference program. They include learning systems, cognition, robotics, perception and action, knowledge rep- sentation and reasoning, and planning and decision making. Many topics deal with uncertainty in various scenarios and incompleteness of knowledge. Summarizing, KI 2010 provides a cross section of recent research in modern AI methods and anthropomatic system applications. We are very grateful that Jos ́ edel Mill ́ an, Hans-Hellmut Nagel, Carl Edward Rasmussen, and David Vernon accepted our invitation to give a talk.
This book constitutes the refereed proceedings of the 38th Annual German Conference on Artificial Intelligence, KI 2015, held in Dresden, Germany, in September 2015. The 15 revised full technical papers presented together with 14 technical communications, 4 doctoral consortium contributions, and 3 keynotes were carefully reviewed and selected from 58 submissions. The conference provides the opportunity to present a wider range of results and ideas that are of interest to the KI audience, including reports about recent own publications, position papers, and previews of ongoing work.
After decades of basic research and more promises than impressive applications, artificial intelligence (AI) is starting to deliver benefits. A convergence of advances is motivating this new surge of AI development and applications. Computer capability as it has evolved from high throughput and high performance computing systems is increasing. AI models and operations research adaptations are becoming more mature, and the world is breeding big data not only from the web and social media but also from the Internet of Things. Organizations around the world have been realizing that there are substantial performance gains and increases in productivity for the use of AI and predictive analytics techniques. Their use is bringing a new era of breakthrough innovation and opportunities. This book, compiles research insights and applications in diverse areas such as manufacturing, supply chain management, pricing, autonomous vehicles, healthcare, ecommerce, and aeronautics. Using classical and advanced tools in AI such as deep learning, particle swarm optimization, support vector machines and genetic programming among others. This is a very distinctive book which discusses important applications using a variety of paradigms from AI and outlines some of the research to be performed. The work supersedes similar books that do not cover as diversified a set of sophisticated applications. The authors present a comprehensive and articulated view of recent developments, identifies the applications gap by quoting from the experience of experts, and details suggested research areas. Artificial Intelligence: Advances in Research and Applications guides the reader through an intuitive understanding of the methodologies and tools for building and modeling intelligent systems. The book's coverage is broad, starting with clustering techniques with unsupervised ensemble learning, where the optimal combination strategy of individual partitions is robust in comparison to the selection of an algorithmic clustering pool. This is followed by a case in a parallel-distributed simulator using deep learning for its configuration. Chapter Three presents a case for autonomous vehicles. Chapter Four discusses the novel use of genetic algorithms with support vector machines. Chapters Five through Thirteen focus on the applications. The book discusses how the use of AI can allow for productivity development and other benefits not just for businesses, but also for economies. Finally, you can find an interesting investigation of the transhuman dimension of AI.
