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: From Motor Learning to Interaction Learning in Robots
  name:
    name part: Sigaud, Olivier.
    role:
      role term: editor.
  name:
    name part: Peters, Jan.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 538 p. online resource.
  abstract: From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.
  table of contents: From Motor Learning to Interaction Learning in Robots -- From Motor Learning to Interaction Learning in Robots -- I: Biologically Inspired Models for Motor Learning -- Distributed Adaptive Control: A Proposal on the Neuronal Organization of Adaptive Goal Oriented Behavior -- Proprioception and Imitation: On the Road to Agent Individuation -- Adaptive Optimal Feedback Control with Learned Internal Dynamics Models -- The SURE_REACH Model for Motor Learning and Control of a Redundant Arm: From Modeling Human Behavior to Applications in Robotics -- Intrinsically Motivated Exploration for Developmental and Active Sensorimotor Learning -- II: Learning Policies for Motor Control -- Learning to Exploit Proximal Force Sensing: A Comparison Approach -- Learning Forward Models for the Operational Space Control of Redundant Robots -- Real-Time Local GP Model Learning -- Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling -- A Bayesian View on Motor Control and Planning -- Methods for Learning Control Policies from Variable-Constraint Demonstrations -- Motor Learning at Intermediate Reynolds Number: Experiments with Policy Gradient on the Flapping Flight of a Rigid Wing -- III: Imitation and Interaction Learning -- Abstraction Levels for Robotic Imitation: Overview and Computational Approaches -- Learning to Imitate Human Actions through Eigenposes -- Incremental Learning of Full Body Motion Primitives -- Can We Learn Finite State Machine Robot Controllers from Interactive Demonstration? -- Mobile Robot Motion Control from Demonstration and Corrective Feedback -- Learning Continuous Grasp Affordances by Sensorimotor Exploration -- Multimodal Language Acquisition Based on Motor Learning and Interaction -- Human-Robot Cooperation Based on Interaction Learning.
  note: edited by Olivier Sigaud, Jan Peters.
  subject:
    topic: Engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computational intelligence
  subject:
    topic: Robotics
  subject:
    topic: Automation
  subject:
    topic: Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Robotics and Automation
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 264
  identifier: 9783642051814
  identifier: http://dx.doi.org/10.1007/978-3-642-05181-4
  record info:
    record creation date: 100301
    record change date: 20151125162253.0
    record identifier: 978-3-642-05181-4