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Contemporary Sensorimotor Theory
This book analyzes the philosophical foundations of sensorimotor theory and discusses the most recent applications of sensorimotor theory to human computer interaction, child’s play, virtual reality, robotics, and linguistics. Why does a circle look curved and not angular? Why does red not sound like a bell? Why, as I interact with the world, is there something it is like to be me? An analytic philosopher might suggest: ``if we ponder the concept of circle we find that it is the essence of a circle to be round’’. However, where does this definition come from? Was it set in stone by the Gods, in other words by divine arbiters of circleness, redness and consciousness? Particularly, with ...
Views Into the Chinese Room
Featuring 19 specially written essays by leading scientists and philosophers, this volume is a state-of-the-art work on the foundations of cognitive science.
Model-Based Machine Learning
Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications th...
Living Jesus
In this richly engaging study of the greatest figure in human history, John Pritchard invites us to encounter the historic -- and living -- Christ.
Swarm Intelligence Algorithms (Two Volume Set)
Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior of animals within specific communities. This can be described as simple behaviors of individuals along with the mechanisms for sharing knowledge between them, resulting in the complex behavior of the entire community. Examples of such behavior can be found in ant colonies, bee swarms, schools of fish or bird flocks. Swarm intelligence algorithms are used to solve difficult optimization problems for which there are no exact solving methods or the use of such methods is impossible, e.g. due to unacceptable computational time. This set comprises two volumes: Swarm...
The Gospel According to Mark
The earliest of the four Gospels, the book portrays Jesus as an enigmatic figure, struggling with enemies, his inner and external demons, and with his devoted but disconcerted disciples. Unlike other gospels, his parables are obscure, to be explained secretly to his followers. With an introduction by Nick Cave.
Joyce's Book of the Dark
“Joyce’s Book of the Dark gives us such a blend of exciting intelligence and impressive erudition that it will surely become established as one of the most fascinating and readable Finnegans Wake studies now available.”—Margot Norris, James Joyce Literary Supplement
Love Unf*cked
From the New York Times bestselling author of Unf*ck Yourself comes tough-love that explains what makes relationships work: you taking responsibility to fix yourself. 'Love is patient, love is blind. . .' Until it's not. Then what? No matter how much advice we get or how much work we do on our 'stuff', nothing ever seems to make the difference. The truth of it is, you're woefully ill-equipped for one of the most life-defining things you will ever take on - being in a committed relationship. Whether you're currently in one, want to be in one, half in-half out, getting over one, married, single, separated, divorced, or just overwhelmed with the whole thing, let's cut through the morass of relationship schtick and put you back in charge. No flowery BS, no woo-woo strategies, systems, or techniques, just real talk, for real people who want a real relationship that actually works.
Pattern Recognition and Machine Learning
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Neural Networks for Pattern Recognition
Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.
