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Artificial Intelligence Using C
412 pages, Paperback
First published January 1, 1987
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About the author
Herbert Schildt
201 books70 followersBest-selling author Herbert Schildt has written extensively about the Java, C++, C, and C# programming languages. His books have sold millions of copies worldwide and have been widely translated. Herb's books have been used in education, corporate training, and individual study.
Although he is interested in all facets of computing, Herb's primary focus is computer languages, especially the standardization of languages. He was a member of the original ANSI committee that standardized the C language in 1989, and he was a member of the ANSI/ISO committee that updated that standard in 1999. He was a member of the original ANSI/ISO committee that standardized C++ in 1998 and he was a member of the ANSI/ISO committee that updated the standard for C++ in 2011.
Herb holds both graduate and undergraduate degrees from the University of Illinois, Urbana/Champaign.
Although he is interested in all facets of computing, Herb's primary focus is computer languages, especially the standardization of languages. He was a member of the original ANSI committee that standardized the C language in 1989, and he was a member of the ANSI/ISO committee that updated that standard in 1999. He was a member of the original ANSI/ISO committee that standardized C++ in 1998 and he was a member of the ANSI/ISO committee that updated the standard for C++ in 2011.
Herb holds both graduate and undergraduate degrees from the University of Illinois, Urbana/Champaign.
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Displaying 1 - 3 of 3 reviews
January 27, 2025
Why read 40-something year old computer texts?
1. Nostalgia - this the stuff I was trying to get my head around back then. Interesting to see where I was at and how it makes sense today.
2. History - those who do not study history are doomed to repeat it, to paraphrase George Santayana.
3. Interest and insight - does this foreshadow Large Language Models?
“...the hit-and-near-miss procedure as a means of capturing information for use by the expert system that was developed in Chapter 3. When reading this chapter, you may have guessed that machine learning is, in the language of computer programmers, a "do-able" task. The main problem is one of magnitude: there is simply so much to learn that it strains both a present-day computer's storage facilities and the patience of the teacher. Perhaps machine learning will become more commonplace when the computer can learn on its own by using sophisticated natural-language processors. (After this is accomplished, one could give the computer the key to the library — and come back when it knows everything!)”
Artificial Intelligence Using C p. 265
Probably not - because LLMs are sheer probability - this implies digestion according to a different logic - but it does recognize that all AI is in our world is embedded in human language.
Schild’s is pre ANSI ‘89 and you learns more re-factoring it to compile today than you do about AI, although I cảm away with a renewed interest in Prolog after hand-coding the search and backtracking structures that Prolog provides.
Schildt also does a good job providing a succinct explanation comprehensible to the non-logician of the difference between propositional and predicate logic. And the latter part of the book provides an insight into how AI was being discussed forty years ago. None of this however, is a compelling reason to read this book. File under whimsical interest.
1. Nostalgia - this the stuff I was trying to get my head around back then. Interesting to see where I was at and how it makes sense today.
2. History - those who do not study history are doomed to repeat it, to paraphrase George Santayana.
3. Interest and insight - does this foreshadow Large Language Models?
“...the hit-and-near-miss procedure as a means of capturing information for use by the expert system that was developed in Chapter 3. When reading this chapter, you may have guessed that machine learning is, in the language of computer programmers, a "do-able" task. The main problem is one of magnitude: there is simply so much to learn that it strains both a present-day computer's storage facilities and the patience of the teacher. Perhaps machine learning will become more commonplace when the computer can learn on its own by using sophisticated natural-language processors. (After this is accomplished, one could give the computer the key to the library — and come back when it knows everything!)”
Artificial Intelligence Using C p. 265
Probably not - because LLMs are sheer probability - this implies digestion according to a different logic - but it does recognize that all AI is in our world is embedded in human language.
Schild’s is pre ANSI ‘89 and you learns more re-factoring it to compile today than you do about AI, although I cảm away with a renewed interest in Prolog after hand-coding the search and backtracking structures that Prolog provides.
Schildt also does a good job providing a succinct explanation comprehensible to the non-logician of the difference between propositional and predicate logic. And the latter part of the book provides an insight into how AI was being discussed forty years ago. None of this however, is a compelling reason to read this book. File under whimsical interest.
July 25, 2025
What a quick fun read! On to the next in the series.
November 22, 2016
A good introduction to artificial intelligence as far as I know. It explains different types of systems and provides complete examples that you can compile yourself.
Displaying 1 - 3 of 3 reviews