• Medientyp: Buch
  • Titel: Multi-agent machine learning : a reinforcement approach
  • Beteiligte: Schwartz, Howard M. [VerfasserIn]
  • Erschienen: Hoboken, NJ: Wiley, 2014
  • Umfang: XI, 242 S.; Ill., graph. Darst
  • Sprache: Englisch
  • ISBN: 9781118362082
  • RVK-Notation: ST 278 : Mensch-Maschine-Kommunikation Software-Ergonomie
    ST 300 : Allgemeines
  • Schlagwörter: Maschinelles Lernen > Mehragentensystem
  • Entstehung:
  • Anmerkungen: Literaturangaben
  • Beschreibung: "Multi-Agent Machine Learning: A Reinforcement Learning Approach is a framework to understanding different methods and approaches in multi-agent machine learning. It also provides cohesive coverage of the latest advances in multi-agent differential games and presents applications in game theory and robotics. Framework for understanding a variety of methods and approaches in multi-agent machine learning. Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering"--

    "Provide an in-depth coverage of multi-player, differential games and Gam theory"--

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