Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This textbook, aimed at junior to senior undergraduate students and first-year graduate students, presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents. By showing how basic approaches fit into a multidimensional design space, readers can learn the fundamentals without losing sight of the bigger picture. The book balances theory and experiment, showing how to link them intimately together, and develops the science of AI together with its engineering applications. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers, and independent learners. AI is a rapidly developing field: this book encapsulates the latest results without being exhaustive and encyclopedic. The text is supported by an online learning environment, AIspace, http://aispace.org, so that students can experiment with the main AI algorithms plus problems, animations, lecture slides, and a knowledge representation system, AIlog, for experimentation and problem solving.
Entrepreneurs and Small and Medium-sized Enterprises (SMEs) have become the darlings of neoliberal development thinking, with the received wisdom being that such enterprises hold the key to the economic transformation of low-income countries. This thinking has profoundly influenced development policy in Rwanda, but has singularly failed to deliver the much anticipated emergence of a new class of entrepreneurs and a vibrant SME sector. This book deconstructs the myths around entrepreneurship and SMEs, and reveals how neoliberal approaches towards microcredit and related programmes have failed to address the economic challenges facing countries like Rwanda. Drawing on his study of successful and aspiring entrepreneurs, Poole identifies the factors associated with successful entrepreneurship. He uncovers the unintended consequences of the entrepreneurship and SME development prescription, and offers key policy insights which have implications for Rwanda and beyond.
Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.
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