Swarm Robotics A Formal Approach Pdf
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Swarm Robotics: A Formal Approach
This book provides an introduction to Swarm Robotics, which is the application of methods from swarm intelligence to robotics. It goes on to present methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, self-assembly, collective construction, and environmental monitoring. The author explains the methodology behind building multiple, simple robots and how the complexity emerges from the multiple interactions between these robots such that they are able to solve difficult tasks. The book can be used as a short textbook for specialized courses or as an introduction to Swarm Robotics for graduate students, researchers, and professionals who want a concise introduction to the field.
Formal Methods and Software Engineering
This book constitutes the refereed proceedings of the 14th International Conference on Formal Engineering Methods, ICFEM 2012, held in Kyoto, Japan, November 2012. The 31 revised full papers together with 3 invited talks presented were carefully reviewed and selected from 85 submissions. The papers address all current issues in formal methods and their applications in software engineering. They are organized in topical sections on concurrency, applications of formal methods to new areas, quantity and probability, formal verification, modeling and development methodology, temporal logics, abstraction and refinement, tools, as well as testing and runtime verification.
Current Problems in Applied Mathematics and Computer Science and Systems
This book is based on the best papers accepted for presentation during the International Conference on Actual Problems of Applied Mathematics and Computer Systems (APAMCS-2022), Russia. The book includes research materials on modern mathematical problems, solutions in the field of scientific computing, data analysis and modular computing. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; solving optimization problems; methods for approximating functions, etc. The studies in data analysis and modular computing include contributions in the field of deep learning, neural networks, mathematical statistics, machine learning methods, residue number system and artificial intelligence. Finally, the book gives insights into the fundamental problems in mathematics education. The book intends for readership specializing in the field of scientific computing, parallel computing, computer technology, machine learning, information security and mathematical education.