Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting ...(展开全部)

A leading artificial intelligence researcher lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as ine...(展开全部)

The most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and of...(展开全部)

Provides avenues for applying functional analysis to the practical study of natural sciences as well as mathematics. Contains worked problems on Hilbert space theory and on Banach spaces and emphasizes concepts, principles, methods and major applications of functional analysis.

Since the September 11, 2001 terrorist attacks on United States soil, the intelligence community has been scrutinized on how it performs its functions. Consequently, the 9/11 Commission made several recommendations on how to improve the quality of intelligence analysis. Those charges and the United States' involvement in a war in Iraq have spawned additional charges of the poli...(展开全部)

Artificial Intelligence is a seemingly neutral technology, but it is increasingly used to manage workforces and make decisions to hire and fire employees. Its proliferation in the workplace gives the impression of a fairer, more efficient system of management. A machine can't discriminate, after all. Augmented Exploitation explores the reality of the impact of AI on workers' li...(展开全部)

Contents: ==User Modeling and Profiling: * Personalization-Privacy Tradeoffs in Adaptive Information Access (B Smyth) * A Deep Evaluation of Two Cognitive User Models for Personalized Search (F Gasparetti & A Micarelli) * Unobtrusive User Modeling for Adaptive Hypermedia (H J Holz et al.) * User Modelling Sharing for Adaptive e-Learning and Intelligent Help (K Kabassi et al.) =...(展开全部)

A revolutionary history of human intelligence that argues that humans know themselves by knowing their machines. We imagine that we are both in control of and controlled by our bodies—autonomous and yet automatic. This entanglement, according to David W. Bates, emerges in the seventeenth century when humans first built and compared themselves with machines. Reading varied think...(展开全部)

Biological evolution is a fact--but the many conflicting theories of evolution remain controversial even today. In 1966, simple Darwinism, which holds that evolution functions primarily at the level of the individual organism, was threatened by opposing concepts such as group selection, a popular idea stating that evolution acts to select entire species rather than individual...(展开全部)

This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problemsThis Learning Path includes content from the following Packt products:Mastering Machine Learning Algorithms by Giuseppe Bonaccorso.Mastering TensorFlow 1.x by Armando Fandango.Deep Learning for Computer Vision by Rajalingappaa Shanmugamani.