Libros Inteligencia artificial, página 2 de 24

Este libro explora la intersección de la neuroética y el derecho digital en Iberoamérica, analizando cómo las tecnologías disruptivas están transformando conceptos jurídicos y éticos. Se examinan enfoques legislativos innovadores, los derechos digitales y neuroderechos, ofreciendo una comprension profunda de como el entorno digital y neurologico impacta la proteccion de derechos fundamentales y la justicia social. Destaca el papel de la dignidad humana como principio rector en la era digital.

This indispensable handbook describes essential foundations of artificial intelligence.Knowledge Representation, which lies at the core of Artificial Intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically.The Handbook of Knowledge Representation is an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field.This book is an essential resource for students, researchers and practitioners in all areas of Artificial Intelligence.- Make your computer smarter.- Handle qualitative and uncertain information.- Improve computational tractability to solve your problems easily.

This text covers all the material needed to understand the principles behind the AI approach to robotics and to program an artificially intelligent robot for applications involving sensing, navigation, planning, and uncertainty. Robin Murphy is extremely effective at combining theoretical and practical rigor with a light narrative touch. In the overview, for example, she touches upon anthropomorphic robots from classic films and science fiction stories before delving into the nuts and bolts of organizing intelligence in robots.Following the overview, Murphy contrasts AI and engineering approaches and discusses what she calls the three paradigms of AI robotics: hierarchical, reactive, and hybrid deliberative/reactive. Later chapters explore multiagent scenarios, navigation and path-planning for mobile robots, and the basics of computer vision and range sensing. Each chapter includes objectives, review questions, and exercises. Many chapters contain one or more case studies showing how the concepts were implemented on real robots. Murphy, who is well known for her classroom teaching, conveys the intellectual adventure of mastering complex theoretical and technical material.An Instructor''s Manual including slides, solutions, sample tests, and programming assignments is available to qualified professors who are considering using the book or who are using the book for class use.

First introduced two decades ago, the term ubiquitous computing is now part of the common vernacular. Ubicomp, as it is commonly called, has grown not just quickly but broadly so as to encompass a wealth of concepts and technology that serves any number of purposes across all of human endeavor. While such growth is positive, the newest generation of ubicomp practitioners and researchers, isolated to specific tasks, are in danger of losing their sense of history and the broader perspective that has been so essential to the fields creativity and brilliance.Under the guidance of John Krumm, an original ubicomp pioneer, Ubiquitous Computing Fundamentals brings together eleven ubiquitous computing trailblazers who each report on his or her area of expertise. Starting with a historical introduction, the book moves on to summarize a number of self-contained topics. Taking a decidedly human perspective, the book includes discussion on how to observe people in their natural environments and evaluate the critical points where ubiquitous computing technologies can improve their lives. Among a range of topics this book examines:- How to build an infrastructure that supports ubiquitous computing applications.- Privacy protection in systems that connect personal devices and personal information.- Moving from the graphical to the ubiquitous computing user interface.- Techniques that are revolutionizing the way we determine a persons location and understand other sensor measurements.While we neednt become expert in every sub-discipline of ubicomp, it is necessary that we appreciate all the perspectives that make up the field and understand how our work can influence and be influenced by those perspectives. This is important, if we are to encourage future generations to be as successfully innovative as the fields originators.

This book addresses the topic of HR analytics focusing especially on demystifying analytics for HR managers from both statistical and computing points of view It presents the evolution and the importance of people analytics in today s workforce management and highlights the motivation for studying business analytics shows the different levels of analytic maturity and discusses real world success stories of business analytics in action through case studies The volume provides the readers with a step by step guide to analyze HR data and interpret the results for strategy formulation Each chapter of the book includes a vignette data driven exercises and real world case studies The authors also introduce the readers to data visualization software Microsoft Power BI as well as elaborates on how to use Tableau Desktop This book would be useful to the students of human resource management organizational behaviour applied psychology social work and sociology It would also serve as very good handbook for practicing business executives helping them to implement data analytics for effective decision making in all kinds of business situations around the world

Transform your organizations approach to AI with tested frameworks from global leaders AI and Innovation: How to Transform Your Business and Outpace the Competition with Generative AI is an expert blueprint on shaping and scaling the AI ecosystem of the future, revealing frameworks already tested and implemented at leading companies including Siemens, GE, and Microsoft. This book contains insight, use cases, tools, and templates to help readers build a brighter future for their organizations based on a fusion of disciplines, new concepts, and foresight thinking. Written by two transformational business leaders, this AI and Innovation shows readers how to create the future of the innovation engine by connecting the dots between technology, change, and business success. The authors discuss topics including: Understanding the core concepts behind AI, including why it matters and what it actually is Generating a roadmap of change, then applying concrete tools and methods to kick-start and anticipate transformational change Transforming the ways of working, collaborating, and realizing new market opportunities Preparing for the future as AI and related technologies continue to progress at a breathtaking pace AI and Innovation is a timely, essential read for business leaders, innovation and strategy managers, and executives seeking state-of-the-art guidance on AI and proven best practices for implementation.

En este libro se introducen los conceptos fundamentales de la Inteligencia Artificial, desde una visión muy orientada al reconocimiento de patrones. El lector podrá encontrar una revisión completa de las tecnicas avanzadas mas usadas en el campo del aprendizaje automatico. El texto se ha enfocado desde un punto de vista eminentemente practico. Las explicaciones teoricas de las diferentes tecnicas se basan en la resolucion de problemas concretos. Los algoritmos estan acompañados de ejemplos, escritos en Python, con aplicaciones directas en ambitos como el procesado de imagenes o el analisis de textos. Los diferentes capitulos comprenden las tecnicas de aprendizaje no supervisado, los metodos de reduccion de la dimensionalidad y extraccion de caracteristicas (PCA, NMF, ICA, LDA, MDS), los principales algoritmos de clasificacion de patrones (probabilisticos, kNN, SVM y Boosting) y diferentes metodos de optimizacion.

El objetivo de esta obra es proporcionar una serie de herramientas autocontenidas que permitan aprender distintos conceptos básicos relacionados con el control automático. El libro se centra en cómo representar cada uno de los conceptos y como formularlos siguiendo un aprendizaje basado en ejemplos.La principal novedad de este libro estriba en que el lector puede estudiar y afianzar conceptos interactuando con herramientas informaticas dirigidas, donde a traves del simple uso del raton se pueden visualizar las distintas representaciones asociadas al problema que se esta estudiando. Estas herramientas interactivas se acompañan de unas fichas donde se explican los objetivos de aprendizaje, un resumen de la teoria asociada a dichos objetivos, las principales referencias bibliograficas, la descripcion detallada de la herramienta y un listado de ejercicios orientados a que el alumno tenga que utilizar la herramienta interactiva en su resolucion.

For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.

Esta obra, enmarcada dentro del Proyecto Natural de Jaén, aborda desde una perspectiva divulgativa el campo científico que fusiona la informática, la tecnología y las matemáticas alrededor de la inteligencia artificial. Se parte de los datos historicos relativos a la formalizacion del razonamiento humano y su traslacion a las maquinas. Ante la pregunta crucial sobre si pueden pensar las maquinas, el libro trata los logros conseguidos en este ambito al tiempo que estudia la inspiracion en la naturaleza para construir sistemas informaticos inteligentes que dan paso a la inteligencia computacional o soft computing, y las utilidades en el analisis inteligente de datos concretadas en el big data, asi como su aplicacion empresarial de la analitica de negocio.

"Este libro sobre Inteligencia Artificial está dirigido, principalmente, a los desarrolladores y no requiere profundos conocimientos en matemáticas. Al hilo de los distintos capítulos la autora presenta las principales tecnicas de Inteligencia Artificial y, para cada una de ellas, su inspiracion, biologica, fisica o incluso matematica, asi como los distintos conceptos y principios (sin entrar en detalles matematicos), con ejemplos y graficos para cada uno de ellos. Los dominios de aplicacion se ilustran mediante aplicaciones reales y actuales. Cada capitulo contiene un ejemplo de implementacion generico, que se completa con una aplicacion practica, desarrollada en C#. Estos ejemplos de codigo genericos son facilmente adaptables a numerosas aplicaciones en C#, bien sea en Silverlight, en Windows Phone, para Windows 8 o incluso en aplicaciones .NET mas clasicas. Las tecnicas de Inteligencia Artificial descritas son:- Los sistemas expertos, que permiten aplicar reglas para tomar decisiones o descubrir nuevos conocimientos.- La logica difusa, que permite controlar sistemas informaticos o mecanicos de manera mucho mas flexible que con los programas tradicionales.- Los algoritmos de busqueda de rutas, entre los cuales el algoritmo A* se utiliza con frecuencia en videojuegos para encontrar los mejores caminos.- Los algoritmos geneticos, que utilizan la potencia de la evolucion para aportar soluciones a problemas complejos.- Los principales maetaheuristicos, entre ellos la busqueda tabu, que permiten encontrar soluciones optimas a problemas de optimizacion, con o sin restricciones.- Los sistemas multi-agentes, que simulan elementos muy simples que permiten conseguir comportamientos emergentes a partir de varios agentes muy sencillos. - Las redes neuronales, capaces de descubrir y reconocer modelos en series historicas, en imagenes o incluso en conjuntos de datos.Para ayudar al lector a pasar de la teoria a la practica, la autora proporciona para su descarga en el sitio web www.ediciones-eni.com siete proyectos de Visual Studio 2013 (uno por cada tecnica de Inteligencia Artificial que se aborda en el libro), desarrollados en C#. Cada proyecto contiene una PCL, para la parte generica, y una aplicacion WPF, para la parte especifica a la aplicacion propuesta.El libro termina con una bibliografia que permite al lector encontrar mas informacion acerca de las diferentes tecnicas, una webgrafia que enumera algunos articulos que presentan aplicaciones reales, un anexo y un indice.Los capitulos del libro:Prologo - Introduccion - Sistemas expertos - Logica difusa - Busqueda de rutas - Algoritmos geneticos - Metaheuristicos de optimizacion - Sistemas multi-agentes - Redes neuronales - Bibliografia - Webgrafia - Anexo"

Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semi-structured and unstructured nature of the Web data. The field has also developed many of its own algorithms and techniques.Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text.The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.

El auge sin precedentes de la inteligencia artificial nos está llevando al diseño de máquinas con capacidades equiparables a las del ser humano. Organizadas como redes de neuronas artificiales, serán capaces de registrar y analizar, mediante algoritmos cada vez mas complejos, los terabytes de informacion de los que disponemos actualmente, hasta llegar a tomar decisiones cada vez mas complejas y actuar de forma cada vez mas racional. Pero ¿podran perfeccionarse a si mismas y crear ultrainteligencias? ¿Estamos ante nuestra ultima generacion como especie dominante?

REVISTA CIDOB D' AFERS 138 DICIEMBRE 2024 La inteligencia artificial (IA) y su desarrollo hiperacelerado suponen un desafío tecnológico, económico, social y geopolítico que los grandes poderes globales abordan desde diversas visiones estrategicas, a vece