rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Introduction to Artificial Intelligence
  name:
    name part: Ertel, Wolfgang.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 316 p. online resource.
  abstract: The ultimate aim of artificial intelligence (A.I.) is to understand intelligence and to build intelligent software and robots that come close to the performance of humans. On their way towards this goal, A.I. researchers have developed a number of quite different subdisciplines. This concise and accessible Introduction to Artificial Intelligence supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The textbook presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: Presents an application-focused and hands-on approach to learning the subject Provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book Supports the text with highlighted examples, definitions, theorems, and illustrative cartoons Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning Contains an extensive bibliography for deeper reading on further topics Supplies additional teaching resources, including lecture slides and training data for learning algorithms, at the website http://www.hs-weingarten.de/~ertel/aibook Students of computer science and other technical natural sciences will find this easy-to-read textbook excellent for self-study, a high-school level of knowledge of mathematics being the only prerequisite to understanding the material. With its extensive tools and bibliography, it is an ideal, quick resource on A.I. Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.
  table of contents: Introduction -- 1: Propositional Logic -- 2: First-order Predicate Logic -- 3: Limitations of Logic -- 4: Logic Programming with PROLOG -- 5: Search, Games and Problem Solving -- 6: Reasoning with Uncertainty -- 7: Machine Learning and Data Mining -- 8: Neural Networks -- 9: Reinforcement Learning -- 10: Solutions for the Exercises.
  note: by Wolfgang Ertel.
  subject:
    topic: Computer science
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Undergraduate Topics in Computer Science
  identifier: 9780857292995
  identifier: http://dx.doi.org/10.1007/978-0-85729-299-5
  record info:
    record creation date: 110317
    record change date: 20170228021831.0
    record identifier: 978-0-85729-299-5