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First Thoughts
Finders, keepers, he thought. But he found the wrong thing. When Daran stumbles upon an abandoned machine, he decides to fix it. He soon discovers that its a gizmo: a machine capable of basic thoughts. These are only owned by the Thought Academy, and they want it backexcept theyre not the only ones that are interested. Daran quickly becomes a pawn in a game he knows nothing about. But when his family is involved, he has no option but to play along. With time running out, he needs to decide whom he sides with and whom he trusts.
Uncertainty in Mechanical Engineering III
Selected, peer reviewed papers from the 3rd International Conference on Uncertainty in Mechanical Engineering (ICUME 2018), November 15 - 16, 2018, Darmstadt, Germany
A Hybrid Physical and Data-drivApproach to Motion Prediction and Control in Human-Robot Collaboration
In recent years, researchers have achieved great success in guaranteeing safety in human-robot interaction, yielding a new generation of robots that can work with humans in close proximity, known as collaborative robots (cobots). However, due to the lack of ability to understand and coordinate with their human partners, the ``co'' in most cobots still refers to ``coexistence'' rather than ``collaboration''. This thesis aims to develop an adaptive learning and control framework with a novel physical and data-driven approach towards a real collaborative robot. The first part focuses on online human motion prediction. A comprehensive study on various motion prediction techniques is presented, i...
Euclides
None
Modelling and Control of Dynamic Systems Using Gaussian Process Models
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed fro...
Efficient Reinforcement Learning Using Gaussian Processes
This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fully Bayesian approach for efficient RL in continuous-valued state and action spaces when no expert knowledge is available. PILCO takes model uncertainties consistently into account during long-term planning to reduce model bias. Second, we propose principled algorithms for robust filtering and smoothing in GP dynamic systems.
Quadratic Forms in Random Variables
Textbook for a one-semester graduate course for students specializing in mathematical statistics or in multivariate analysis, or reference for theoretical as well as applied statisticians, confines its discussion to quadratic forms and second degree polynomials in real normal random vectors and matr
Avant Garde Design
The first book in English devoted to the contribution made by the Netherlands to avant-garde design, this extensively illlustrated book covers the innovative period of Dutch decorative arts between 1880-1940
