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Knowing our World: An Artificial Intelligence Perspective

Name: Knowing our World: An Artificial Intelligence Perspective
Brand: Springer Nature Switzerland AG
SKU: 9783030718756
Price: 168.63 EUR
Availability: InStock

Автор: George F. Luger

Език:

Корици: С меки корици

Издател: Springer Nature Switzerland AG

Наличност: Външен склад

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168.63 € 329.81 лв

Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, co...

Информация за книгата

Автор

George F. Luger

Език

Английски език

Корици

Книга - С меки корици

Издадена

2022

страници

256

EAN

9783030718756

Enbook ID

39302252

Издател

Springer Nature Switzerland AG

Теглоt

424

Размери

233 x 155 x 18

Пълно описание

Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind's history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals.Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building.The book's second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use.The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.

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