Prolog and Artificial Intelligence: A Practical Guide to Building Intelligent, Rule-Based, and Explainable Systems

Modern AI is facing a crisis of explainability . We are building powerful systems that deny loans, recommend medical treatments, and control autonomous vehicles... but they can't answer the simple question, Why?

This book flips the script. Your journey begins not with complex math, but with the simple, declarative beauty of a logical fact: parent(john, mary). You'll quickly master how Prolog thinks through its powerful unification and backtracking engines—the gears of its logical mind.

But this is just the beginning. The real journey starts when you encode the common sense of a human expert into rules, building an AI that can diagnose medical symptoms. You'll teach your program to solve complex logic puzzles in seconds. You'll write a grammar that can parse English.

The final payoff? You won't just build an AI. You'll build an auditable one. You will learn to retrofit your brain with a custom explanation engine, teaching it to answer not only How do you know? but also the even more powerful question: Why not ?

What's inside

This book is a complete curriculum for mastering symbolic AI. You will learn:

The Foundations: Understand the critical difference between the black box (neural networks) and the glass box (Prolog). The Thinking Engine: Master Unification (pattern-matching) and Backtracking (the search for truth), the two core mechanics of all logic programming. Building Your First AI: Build a complete expert system from scratch, encoding a doctor's knowledge into logical rules. Classic AI Projects: Write programs that can find their way out of any maze, solve complex logic puzzles (like the Zebra Puzzle), and even play a perfect game of Tic-Tac-Toe using the minimax algorithm. Understanding Human Language: Use Definite Clause Grammars (DCGs) to build a parser that translates English sentences into logical database queries. The Glass Box Payoff: The book's climax. You'll build your own Explainable AI (XAI) engine from the ground up, teaching your system to generate How? and Why Not? explanations for its own conclusions. Connecting to the World: Learn how to use Prolog as a brain from other languages (like Python ) and how to build a stand-alone JSON API web server inside Prolog itself. The Future: Get a brief look at the exciting new field of Neuro-Symbolic AI , the hybrid that combines Prolog's logic with the power of deep learning. Who it's meant for

This book is for you if:

You are a programmer (in Python, Java, C++, or JavaScript) who is frustrated by the black box and wants to understand the other half of artificial intelligence. You are a data scientist or AI practitioner who needs to build models that are auditable, verifiable, and can explain their decisions. You are a computer science student who wants a deep, practical, and applied understanding of logic programming and AI theory. You are a hobbyist who loves puzzles, logic, and wants to learn how to build an engine that reasons . You don't need any prior Prolog experience. All you need is a curious mind and a desire to know why .

Don't just build AI that works . Build AI you can understand .

Stop being a user of black box magic and become an architect of glass box logic. This book is your practical guide to building systems you can question, audit, and trust.

Your journey into real, explainable AI begins now. Get the book and learn to build systems that can finally answer, Why?