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This book constitutes the refereed proceedings of the 25th International Conference on Case-Based Reasoning Research and Development, ICCBR 2017, held in Trondheim, Norway, in June 2017. The 27 full papers presented together with 3 keynote presentations were carefully reviewed and selected from 38 submissions. The theme of ICCBR-2017, "Analogy for Reuse", was highlighted in several events. These papers, which are included in the proceedings, address many themes related to the theory and application of case-based reasoning, analogical reasoning, CBR and Deep Learning, CBR in the Health Sciences, Computational Analogy, and Process-Oriented CBR.
Computer science. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Application software. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computer Applications. --- Data Mining and Knowledge Discovery. --- Information Storage and Retrieval. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Informatics --- Computer software --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Database searching --- Science --- Information storage and retrieva. --- Artificial Intelligence. --- Information retrieval. --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval
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"This book focuses on a subtopic of Explainable AI (XAI) called Explainable Agency (EA), which involves producing records of decisions made during an agent's reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for them. We distinguish explainable agency from Interpretable Machine Learning (IML), another branch of XAI that focuses on providing insight (typically, for an ML expert) concerning a learned model and its decisions. In contrast, explainable agency typically involves a broader set of AI-enabled techniques, systems, and stakeholders (e.g., end users) where the explanations provided by EA agents are best evaluated in the context of human subject studies. The chapters of this book explore the concept of endowing intelligent agents with explainable agency, which is crucial for agents to be trusted by humans in critical domains such as finance, self-driving vehicles, and military operations. This book presents the work of researchers from a variety of perspectives and describes challenges, recent research results, lessons learned from applications, and recommendations for future research directions in EA. The historical perspectives of explainable agency and the importance of interactivity in explainable systems are also discussed. Ultimately, this book aims to contribute to the successful partnership between humans and AI systems."-- Provided by publisher.
Reinforcement learning. --- Artificial intelligence. --- Decision making.
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