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 Universität 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.
人気のある作家
J KING (12) JJ TAM (12) yang hu (11) Al Sweigart (8) Mojang AB (8) desti publishhings (7) Hidenori Kusaka (6) John Bach (6) Walter Leal Filho (6) Amanda Lange Salvia (5) Anabela Marisa Azul (5) Andrea Vedaldi (5) Halonjash Publications (5) Hiro Ainana (5) Horst Bischof (5) Intelligent Feather Publications (5) Jan-Michael Frahm (5) Michael W. Lucas (5) Andrew Park (4) Benjamin Smith (4)最適なファイルサイズ
10531 KB 1079 KB 1116 KB 1233 KB 2661 KB 370 KB 484 KB 536 KB 649 KB 738 KB 790 KB 10049 KB 1006 KB 10137 KB 1016 KB 102097 KB 1029 KB 10325 KB 1032 KB 1035 KB