Advanced Searches, Knowledge Representation and Reasoning: From Intelligent Search to Logical and Probabilistic Reasoning (Artificial Intelligence Series)

Advanced Searches, Knowledge Representation and Reasoning – Volume 2 explores the techniques that allow Artificial Intelligence systems to search for solutions, represent knowledge, and reason from available information.

The book covers advanced search techniques, constraint satisfaction, game playing, minimax, alpha-beta pruning, propositional logic, first-order logic, inference rules, unification, resolution, forward chaining, backward chaining, and knowledge-based systems. It also introduces probabilistic reasoning and Bayes' theorem, helping readers understand how AI systems handle uncertainty and incomplete information.

Written in a clear and beginner-friendly style, the book uses examples, step-by-step explanations, algorithms, and intuitive illustrations to make complex AI concepts accessible to students and self-learners.

This volume is suitable for engineering and computer science students, AI learners, educators, and anyone seeking a structured introduction to search, knowledge representation, logical reasoning, and probabilistic reasoning in Artificial Intelligence.