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In cognitive science, artificial intelligence, psychology, and education, a growing body of research supports the view that the learning process is strongly influenced by the learner's goals. The fundamental tenet of goal-driven learning is that learning is largely an active and strategic process in which the learner, human or machine, attempts to identify and satisfy its information needs in the context of its tasks and goals, its prior knowledge, its capabilities, and environmental opportunities for learning. This book brings together a diversity of research on goal-driven learning to establish a broad, interdisciplinary framework that describes the goal-driven learning process. It collects and solidifies existing results on this important issue in machine and human learning and presents a theoretical framework for future investigations. The book opens with an an overview of goal-driven learning research and computational and cognitive models of the goal-driven learning process. This introduction is followed by a collection of fourteen recent research articles addressing fundamental issues of the field, including psychological and functional arguments for modeling learning as a deliberative, planful process; experimental evaluation of the benefits of utility-based analysis to guide decisions about what to learn; case studies of computational models in which learning is driven by reasoning about learning goals; psychological evidence for human goal-driven learning; and the ramifications of goal-driven learning in educational contexts. The second part of the book presents six position papers reflecting ongoing research and current issues in goal-driven learning. Issues discussed include methods for pursuing psychological studies of goal-driven learning, frameworks for the design of active and multistrategy learning systems, and methods for selecting and balancing the goals that drive learning. A Bradford Book.

Computational learning theory. --- Computational learning theory --- Machine learning --- E-books --- Engineering & Applied Sciences --- Computer Science --- COMPUTER SCIENCE/Artificial Intelligence

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This book constitutes the refereed proceedings of the 8th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2014, held in Hangzhou, China, in October 2014. The 32 revised papers presented were carefully reviewed and selected from more than 70 submissions. They are organized in topical sections on machine learning, data mining, web mining, multi-agent systems, automatic reasoning, decision algorithms, multimedia, pattern recognition, and information security.

Computer science. --- Computer logic. --- Mathematical logic. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Pattern recognition. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Data Mining and Knowledge Discovery. --- Mathematical Logic and Formal Languages. --- Information Storage and Retrieval. --- Pattern Recognition. --- Logics and Meanings of Programs. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Computer science logic --- Logic, Symbolic and mathematical --- Informatics --- Science --- Optical pattern recognition. --- Logic design. --- Artificial Intelligence. --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Switching theory --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- 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 --- Artificial intelligence --- Data mining --- Logic, Symbolic and mathematical. --- Pattern perception.

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Human sciences (algemeen) --- Mathematical logic --- Social sciences (general) --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- informatica --- sociale wetenschappen --- wiskunde --- logica --- robots