A Practical Guide To Designing Expert Systems
Condition: SECONDHAND
This is a secondhand book. The jacket image is a photograph of the exact copy we have in stock. This image shows the condition of this book. Further condition remarks are below.
Condition remarks:
Book: Good
Jacket: Very good
Pages: Good
At the dawn of the artificial intelligence revolution, A Practical Guide to Designing Expert Systems stands as a landmark technical manual that instructs engineers, researchers, and computer scientists in the methodical construction of knowledge-based systems. The book chronicles the full lifecycle of expert system development — from knowledge acquisition and representation to inference engine design and system validation — presenting complex AI concepts with clarity and structured precision. Weiss and Kulikowski draw on their deep expertise in machine learning and medical AI to ground each concept in real-world application, making abstract computational theory immediately accessible and actionable. Written at a pivotal moment when expert systems were transitioning from academic curiosity to industrial tool, this volume argues persuasively for a disciplined, engineering-driven approach to AI system design. The authors illustrate the interplay between domain knowledge and computational logic, detailing how symbolic reasoning can be harnessed to replicate expert human decision-making. Rooted in both theoretical rigor and hands-on pragmatism, this guide remains a foundational text for anyone seeking to understand the principles that underpinned an era of transformative technological ambition — and one that continues to echo in today's modern AI systems.
Author: Sholom M. Weiss And Casimir A. Kulikowski
Format: Hardback
Genre: Science
Condition remarks:
Book: Good
Jacket: Very good
Pages: Good
At the dawn of the artificial intelligence revolution, A Practical Guide to Designing Expert Systems stands as a landmark technical manual that instructs engineers, researchers, and computer scientists in the methodical construction of knowledge-based systems. The book chronicles the full lifecycle of expert system development — from knowledge acquisition and representation to inference engine design and system validation — presenting complex AI concepts with clarity and structured precision. Weiss and Kulikowski draw on their deep expertise in machine learning and medical AI to ground each concept in real-world application, making abstract computational theory immediately accessible and actionable. Written at a pivotal moment when expert systems were transitioning from academic curiosity to industrial tool, this volume argues persuasively for a disciplined, engineering-driven approach to AI system design. The authors illustrate the interplay between domain knowledge and computational logic, detailing how symbolic reasoning can be harnessed to replicate expert human decision-making. Rooted in both theoretical rigor and hands-on pragmatism, this guide remains a foundational text for anyone seeking to understand the principles that underpinned an era of transformative technological ambition — and one that continues to echo in today's modern AI systems.