توضیحات
Written by Robert Kowalski, one of the pioneers of logic programming and the creator of the SLD-resolution principle used in Prolog, this book reexamines and updates the ideas presented in his original work Logic for Problem Solving (1979). It connects logical theory, human reasoning, and AI systems, presenting a unified framework for solving problems logically and computationally.
The book introduces a dual model of reasoning:
Knowledge Representation through Logic – describing what is true.
Goal-Directed Problem Solving – reasoning about what actions to take.
Kowalski blends philosophy, logic, and computer science to show how intelligent behavior can be modeled as the interaction between beliefs (declarative knowledge) and goals (procedural reasoning).
Key topics include:
Foundations of Logic Programming: Understanding logical syntax, semantics, and inference rules.
Declarative vs. Procedural Knowledge: How facts and actions interact in reasoning systems.
Resolution and Proof Strategies: Revisiting resolution-based problem-solving and SLD-resolution.
Abductive Logic Programming: Using logic to infer explanations and predict causes.
Reactive and Agent-Based Systems: Applying logic to autonomous agents that reason and act.
Cognitive Modeling: Linking logical inference to human problem-solving and decision-making.
Applications in AI: Knowledge-based systems, planning, and intelligent automation.
Comparison with Other Paradigms: How logic complements machine learning and statistical AI.
Through theoretical discussion and practical examples, the book demonstrates how logical reasoning remains fundamental to AI, offering a clear perspective on how logic can drive intelligent action, reasoning, and learning in both machines and humans.
نقد و بررسیها
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