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A comprehensive introduction to using the tools and techniques of neuroscience to understand how consumers make decisions about purchasing goods and services.Contrary to the assumptions of economists, consumers are not always rational actors who make decisions in their own best interests. The new field of behavioral economics draws on the insights of psychology to study non-rational decision making. The newer field of consumer neuroscience draws on the findings, tools, and techniques of neuroscience to understand how consumers make judgments and decisions. This book is the first comprehensive treatment of consumer neuroscience, suitable for classroom use or as a reference for business and marketing practitioners.After an overview of the field, the text offers the background on the brain and physiological systems necessary for understanding how they work in the context of decision making and reviews the sensory and perceptual mechanisms that govern our perception and experience. Chapters by experts in the field investigate tools for studying the brain, including fMRI, EEG, eye-tracking, and biometrics, and their possible use in marketing. The book examines the relation of attention, memory, and emotion to consumer behavior; cognitive factors in decision making; and the brain's reward system. It describes how consumers develop implicit associations with a brand, perceptions of pricing, and how consumer neuroscience can encourage healthy behaviors. Finally, the book considers ethical issues raised by the application of neuroscience tools to marketing.ContributorsFabio Babiloni, Davide Baldo, David Brandt, Moran Cerf, Yuping Chen, Patrizia Cherubino, Kimberly Rose Clark, Maria Cordero-Merecuana, William A. Cunningham, Manuel Garcia-Garcia, Ming Hsu, Ana Iorga, Philip Kotler, Carl Marci, Hans Melo, Kai-Markus Müller, Brendan Murray, Ingrid L. C. Nieuwenhuis, Graham Page, Hirak Parikh, Dante M. Pirouz, Martin Reimann, Neal J. Roese, Irit Shapira-Lichter, Daniela Somarriba, Julia Trabulsi, Arianna Trettel, Giovanni Vecchiato, Thalia Vrantsidis, Sarah Walker

A comprehensive overview of the theory of stochastic processes and its connections to asset pricing, accompanied by some concrete applications.

An introduction to economic applications of the theory of continuous-time finance that strikes a balance between mathematical rigor and economic interpretation of financial market regularities.

The development of an epistemology that explains how science and art embody and convey understanding.Philosophy valorizes truth, holding that there can never be epistemically good reasons to accept a known falsehood, or to accept modes of justification that are not truth conducive. How can this stance account for the epistemic standing of science, which unabashedly relies on models, idealizations, and thought experiments that are known not to be true? In True Enough, Catherine Elgin argues that we should not assume that the inaccuracy of models and idealizations constitutes an inadequacy. To the contrary, their divergence from truth or representational accuracy fosters their epistemic functioning. When effective, models and idealizations are, Elgin contends, felicitous falsehoods that exemplify features of the phenomena they bear on. Because works of art deploy the same sorts of felicitous falsehoods, she argues, they also advance understanding.Elgin develops a holistic epistemology that focuses on the understanding of broad ranges of phenomena rather than knowledge of individual facts. Epistemic acceptability, she maintains, is a matter not of truth-conduciveness, but of what would be reflectively endorsed by the members of an idealized epistemic community—a quasi-Kantian realm of epistemic ends.

The career of the pioneering designer Muriel Cooper, whose work spanned media from printed book to software interface; generously illustrated in color.Muriel Cooper (1925-1994) was the pioneering designer who created the iconic MIT Press colophon (or logo)—seven bars that represent the lowercase letters "mitp” as abstracted books on a shelf. She designed a modernist monument, the encyclopedic volume The Bauhaus (1969), and the graphically dazzling and controversial first edition of Learning from Las Vegas (1972). She used an offset press as an artistic tool, worked with a large-format Polaroid camera, and had an early vision of e-books. Cooper was the first design director of the MIT Press, the cofounder of the Visible Language Workshop at MIT, and the first woman to be granted tenure at MIT's Media Lab, where she developed software interfaces and taught a new generation of designers. She began her four-decade career at MIT by designing vibrant printed flyers for the Office of Publications; her final projects were digital. This lavishly illustrated volume documents Cooper's career in abundant detail, with prints, sketches, book covers, posters, mechanicals, student projects, and photographs, from her work in design, teaching, and research at MIT.A humanist among scientists, Cooper embraced dynamism, simultaneity, transparency, and expressiveness across all the media she worked in. More than two decades after her career came to a premature end, Muriel Cooper's legacy is still unfolding. This beautiful slip-cased volume, designed by Yasuyo Iguchi, looks back at a body of work that is as contemporary now as it was when Cooper was experimenting with IBM Selectric typewriters. She designed design's future.

The first textbook on micron-scale mobile robotics, introducing the fundamentals of design, analysis, fabrication, and control, and drawing on case studies of existing approaches.

Concise introductions to the main issues in energy policy and their interaction with environmental policies in the EU.

A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data.After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Perceptrons - the first systematic study of parallelism in computation - has remained a classical work on threshold automata networks for nearly two decades.

An analysis of how responsive governance has shaped the evolution of global fisheries in cyclical patterns of depletion and rebuilding dubbed the "management treadmill."

An argument that the commons is neither tragedy nor paradise but can be a way to understand environmental sustainability.

What happens when natural gas drilling moves into an urban area: how communities in North Texas responded to the environmental and health threats of fracking.

Physicians, philosophers, and theologians consider how to address death and dying for a diverse population in a secularized century.

An economist's perspective on the nuts and bolts of economic policymaking, based on his experience as the Chief Economic Adviser in India.

How big data is transforming the creative industries, and how those industries can use lessons from Netflix, Amazon, and Apple to fight back.

How better information and better access to it improves the quality of our decisions and makes for a more vibrant participatory society.

The work of art's mattering and materialization in a globalized world, with close readings of works by Takahashi Murakami, Andreas Gursky, Thomas Hirschhorn, and others.

How technologies can get it wrong in sports, and what the consequences are-referees undermined, fans heartbroken, and the illusion of perfect accuracy maintained.

Why our brains aren't built for media multitasking, and how we can learn to live with technology in a more balanced way.

How right-wing political entrepreneurs around the world use religious offense-both given and taken-to mobilize supporters and marginalize opponents.

An integrated, holistic model for infrastructure planning and design in developing countries.

An exploration of the need for innovative mechanisms of governance in an era when human actions are major drivers of environmental change.

Using formal systems to represent and reason about uncertainty.

Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field.