Leverage Control

Two leading figures from the world of finance show how progressives can take their money away from conservative financial institutions and put it to good, lasting social use

Improve The Safety Stock in Your Supply Chain & Reduce Your Company's Operating Costs and Risk.

In today’s world of interconnected and "always-on" information, companies that succeed are those that compete by leveraging the advantage of strategic control points. A strategic control point is a part of a market where, if controlled by one party, it can be used to leverage power elsewhere. This can occur throughout the supply chain, in a related business, or even in an unrelated market.

One important robotics problem is “How can one program a robot to perform a task”? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots.

This book is devoted to the study of engineering and control technologies for the cyber-physical systems development. This book defines the approaches in the engineering leverage the exploitation of artificial intelligence and most urgent computing methods. The authors study the activities allows for the developing new and perspective concepts of robotics systems combining various machine learning methods, uncertainty explanation approaches, computer vision and unmanned aerial systems control technologies including artificial neural networks and simulation modeling by addressing a large scale of applications.

A series of practical recipes to simplify the Git learning experience and increase your productivity when using Git version control