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Classification in the Wild
Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.
Cognitive Operations
This book examines how people make decisions under risk and uncertainty in operational settings and opens the black box by specifying the cognitive processes that lead to human behavior. Drawing on economics, psychology and artificial intelligence, the book provides an innovative perspective on behavioral operations. It shows how to build optimization as well as heuristic models for describing human behavior and how to compare such models on various dimensions such as predictive power and transparency, as well as discussing interventions for improving human behavior. This book will be particularly valuable to academics and practitioners who seek to select a modeling approach that suits the operational decision at hand.
Data Science for Economics and Finance
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics rela...
Artificial Intelligence in Finance
This book provides a comprehensive analysis of the primary challenges, opportunities and regulatory developments associated with the use of artificial intelligence (AI) in the financial sector. It will show that, while AI has the potential to promote a more inclusive and competitive financial system, the increasing use of AI may bring certain risks and regulatory challenges that need to be addressed by regulators and policymakers.
Regulating Financial Innovation
This book explores the impact of 'Fintech' on the information asymmetry between the financial regulator and the markets. It details the growing regulatory mismatch and how Fintech exacerbates the “pacing problem”, where the regulator struggles to keep up with innovation. With information as a point of reference, the book adds a new perspective on the latest phenomenon in financial innovation and presents a novel framework for navigating structural changes in the financial sector. Based on this analysis, a number of proposals to reduce the information gap and avoid regulatory mismatch are discussed. Thereby, new and promising regulatory concepts, such as regulatory sandboxes and SupTech applications are also covered. This book provides a practical framework for regulatory responses to financial innovation. It will be relevant to researchers and practitioners interested in financial technology and regulation.
Insect Diapause
Captures the full scope of the literature, integrating ecological and molecular mechanisms that enable insects to enter a dormant state.
The Reed Review
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Wildlife Review
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