Machine Behavior Design And Analysis
Machine Behavior Design And Analysis

Author: Yinyan Zhang

Publisher: Springer Nature

Published: 2020-03-13

Total Pages: 193

ISBN-13: 9811532311

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In this book, we present our systematic investigations into consensus in multi-agent systems. We show the design and analysis of various types of consensus protocols from a multi-agent perspective with a focus on min-consensus and its variants. We also discuss second-order and high-order min-consensus. A very interesting topic regarding the link between consensus and path planning is also included. We show that a biased min-consensus protocol can lead to the path planning phenomenon, which means that the complexity of shortest path planning can emerge from a perturbed version of min-consensus protocol, which as a case study may encourage researchers in the field of distributed control to rethink the nature of complexity and the distance between control and intelligence. We also illustrate the design and analysis of consensus protocols for nonlinear multi-agent systems derived from an optimal control formulation, which do not require solving a Hamilton-Jacobi-Bellman (HJB) equation. The book was written in a self-contained format. For each consensus protocol, the performance is verified through simulative examples and analyzed via mathematical derivations, using tools like graph theory and modern control theory. The book’s goal is to provide not only theoretical contributions but also explore underlying intuitions from a methodological perspective.

Behavior Analysis with Machine Learning Using R
Behavior Analysis with Machine Learning Using R

Author: Enrique Garcia Ceja

Publisher: CRC Press

Published: 2021-11-26

Total Pages: 434

ISBN-13: 1000484238

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Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

A Decadal Survey of the Social and Behavioral Sciences
A Decadal Survey of the Social and Behavioral Sciences

Author: ENGINEERING NATIONAL ACADEMIES OF SCIENCES (AND M.)

Publisher:

Published: 2019

Total Pages: 26

ISBN-13: 9780309670333

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"The Digest Version of A Decadal Survey of the Social and Behavioral Sciences: A Research Agenda for Advancing Intelligence Analysis summarizes the most important ideas from the full report for the Intelligence Community to consider in the coming decade. This volume provides an overview of the primary opportunities that research in the social and behavioral sciences offers for strengthening national security, specifically the work of the intelligence analyst, and the conclusions and recommendations of the Committee on a Decadal Survey of Social and Behavioral Sciences for Applications to National Survey. This digest version is a succinct roadmap to the critical contribution researchers from these fields make to national security"--Publisher's description

Machine Component Analysis with MATLAB
Machine Component Analysis with MATLAB

Author: Dan B. Marghitu

Publisher: Butterworth-Heinemann

Published: 2019-03-15

Total Pages: 232

ISBN-13: 012804229X

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Machine Design Analysis with MATLAB is a highly practical guide to the fundamental principles of machine design which covers the static and dynamic behavior of engineering structures and components. MATLAB has transformed the way calculations are made for engineering problems by computationally generating analytical calculations, as well as providing numerical calculations. Using step-by-step, real world example problems, this book demonstrates how you can use symbolic and numerical MATLAB as a tool to solve problems in machine design. This book provides a thorough, rigorous presentation of machine design, augmented with proven learning techniques which can be used by students and practicing engineers alike. Comprehensive coverage of the fundamental principles in machine design Uses symbolical and numerical MATLAB calculations to enhance understanding and reinforce learning Includes well-designed real-world problems and solutions

Behavior Trees in Robotics and AI
Behavior Trees in Robotics and AI

Author: Michele Colledanchise

Publisher: CRC Press

Published: 2018-07-20

Total Pages: 316

ISBN-13: 0429950896

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Behavior Trees (BTs) provide a way to structure the behavior of an artificial agent such as a robot or a non-player character in a computer game. Traditional design methods, such as finite state machines, are known to produce brittle behaviors when complexity increases, making it very hard to add features without breaking existing functionality. BTs were created to address this very problem, and enables the creation of systems that are both modular and reactive. Behavior Trees in Robotics and AI: An Introduction provides a broad introduction as well as an in-depth exploration of the topic, and is the first comprehensive book on the use of BTs. This book introduces the subject of BTs from simple topics, such as semantics and design principles, to complex topics, such as learning and task planning. For each topic, the authors provide a set of examples, ranging from simple illustrations to realistic complex behaviors, to enable the reader to successfully combine theory with practice. Starting with an introduction to BTs, the book then describes how BTs relate to, and in many cases, generalize earlier switching structures, or control architectures. These ideas are then used as a foundation for a set of efficient and easy to use design principles. The book then presents a set of important extensions and provides a set of tools for formally analyzing these extensions using a state space formulation of BTs. With the new analysis tools, the book then formalizes the descriptions of how BTs generalize earlier approaches and shows how BTs can be automatically generated using planning and learning. The final part of the book provides an extended set of tools to capture the behavior of Stochastic BTs, where the outcomes of actions are described by probabilities. These tools enable the computation of both success probabilities and time to completion. This book targets a broad audience, including both students and professionals interested in modeling complex behaviors for robots, game characters, or other AI agents. Readers can choose at which depth and pace they want to learn the subject, depending on their needs and background.

Designing Stable Finite State Machine Behaviors Using Phase Plane Analysis and Variable Structure Control
Designing Stable Finite State Machine Behaviors Using Phase Plane Analysis and Variable Structure Control

Author:

Publisher:

Published: 1998

Total Pages: 10

ISBN-13:

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This paper discusses how phase plane analysis can be used to describe the overall behavior of single and multiple autonomous robotic vehicles with finite state machine rules. The importance of this result is that one can begin to design provably asymptotically stable group behaviors from a set of simple control laws and appropriate switching points with decentralized variable structure control. The ability to prove asymptotically stable group behavior is especially important for applications such as locating military targets or land mines.

Behavioral Analysis and Measurement Methods
Behavioral Analysis and Measurement Methods

Author: David Meister

Publisher: Wiley-Interscience

Published: 1985-03-26

Total Pages: 534

ISBN-13:

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This book consolidates and describes, for the first time, all of the individual behavioral methods used to study work performance.

Behavioral Data Analysis with R and Python
Behavioral Data Analysis with R and Python

Author: Florent Buisson

Publisher: "O'Reilly Media, Inc."

Published: 2021-06-15

Total Pages: 361

ISBN-13: 1492061344

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Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way

Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms
Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms

Author: Sandeep Kumar

Publisher: John Wiley & Sons

Published: 2021-11-23

Total Pages: 400

ISBN-13: 1119792088

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COGNITIVE BEHAVIOR AND HUMAN COMPUTER INTERACTION BASED ON MACHINE LEARNING ALGORITHMS The objective of this book is to provide the most relevant information on Human-Computer Interaction to academics, researchers, and students and for those from industry who wish to know more about the real-time application of user interface design. Human-computer interaction (HCI) is the academic discipline, which most of us think of as UI design, that focuses on how human beings and computers interact at ever-increasing levels of both complexity and simplicity. Because of the importance of the subject, this book aims to provide more relevant information that will be useful to students, academics, and researchers in the industry who wish to know more about its real-time application. In addition to providing content on theory, cognition, design, evaluation, and user diversity, this book also explains the underlying causes of the cognitive, social and organizational problems typically devoted to descriptions of rehabilitation methods for specific cognitive processes. Also described are the new modeling algorithms accessible to cognitive scientists from a variety of different areas. This book is inherently interdisciplinary and contains original research in computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Since machine learning research has already been carried out for a decade in various applications, the new learning approach is mainly used in machine learning-based cognitive applications. Since this will direct the future research of scientists and researchers working in neuroscience, neuroimaging, machine learning-based brain mapping, and modeling, etc., this book highlights the framework of a novel robust method for advanced cross-industry HCI technologies. These implementation strategies and future research directions will meet the design and application requirements of several modern and real-time applications for a long time to come. Audience: A wide range of researchers, industry practitioners, and students will be interested in this book including those in artificial intelligence, machine learning, cognition, computer programming and engineering, as well as social sciences such as psychology and linguistics.

Psychology of System Design
Psychology of System Design

Author: D. Meister

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 560

ISBN-13: 1483295923

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This is a book about systems, including: systems in which humans control machines; systems in which humans interact with humans and the machine component is relatively unimportant; systems which are heavily computerized and those that are not; and governmental, industrial, military and social systems. The book deals with both traditional systems like farming, fishing and the military, and with systems just now tentatively emerging, like the expert and the interactive computer system. The emphasis is on the system concept and its implications for analysis, design and evaluation of these many different types of systems. The book attempts to make three major points: 1. System design, and particularly computer system design, must fit into and be directed by a comprehensive theory of system functioning. 2. Interactive computer design models itself upon our knowledge of how humans function. 3. Highly sophisticated interactive computer systems are presently mostly research vehicles, they are vastly different to general purpose, commercially available word processors and personal computers. The book represents an interdisciplinary approach, the author has used psychological, organizational, human factors, and engineering sources. The book is not a "how to do it" book but it is intended to stimulate thinking about the larger context in which systems, particularly computer systems of the future, should be designed and used.