@article{1433285,
      recid = {1433285},
      author = {Belousov, Boris, and Abdulsamad, Hany, and Klink, Pascal,  and Parisi, Simone, and Peters, Jan,},
      title = {Reinforcement learning algorithms : analysis and  applications /},
      pages = {1 online resource (viii, 206 pages) :},
      abstract = {This book reviews research developments in diverse areas  of reinforcement learning such as model-free actor-critic  methods, model-based learning and control, information  geometry of policy searches, reward design, and exploration  in biology and the behavioral sciences. Special emphasis is  placed on advanced ideas, algorithms, methods, and  applications. The contributed papers gathered here grew out  of a lecture course on reinforcement learning held by Prof.  Jan Peters in the winter semester 2018/2019 at Technische  Universitat Darmstadt. The book is intended for  reinforcement learning students and researchers with a firm  grasp of linear algebra, statistics, and optimization.  Nevertheless, all key concepts are introduced in each  chapter, making the content self-contained and accessible  to a broader audience.},
      url = {http://library.usi.edu/record/1433285},
      doi = {https://doi.org/10.1007/978-3-030-41188-6},
}