"Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one or two semester university course on AI, as well as an invaluable reference for researchers in the field or practitioners wishing to employ the power of current AI techniques in their work."--BOOK JACKET.
Luger frames AI fundamentally as the study of how to represent and solve complex problems. He introduces the idea that much of AI can be understood as searching for solutions in large, often intractable, problem spaces. The book systematically explores different search strategies—such as uninformed, heuristic, and adversarial search—emphasizing their strengths, limitations, and appropriate contexts. This focus on problem-solving provides a unifying thread for the diverse techniques covered throughout the text.
A core argument in the book is that the effectiveness of AI hinges on how knowledge is represented. Luger surveys various methods—semantic nets, frames, logic, and production systems—showing how each enables different kinds of reasoning. He stresses that the choice of representation impacts not only what can be expressed but also the efficiency and success of algorithms, connecting theory directly to practical system design.
