About This Book
Artificial Intelligence (AI) is a multidisciplinary field of computer science aimed at creating machines capable of
performing tasks that typically require human intelligence. These tasks include reasoning, learning, problemsolving,
and decision-making. AI systems are designed to mimic cognitive functions such as understanding
language, recognizing patterns, and adapting to new situations. AI applications span a wide range of
industries, from healthcare and finance to transportation and entertainment, revolutionizing the way tasks are
automated and problems are solved. Logic programming is a paradigm of programming based on formal logic.
It allows problems to be expressed in terms of facts, rules, and queries, relying on logic to deduce conclusions or
find solutions. One of the most prominent logic programming languages is Prolog (Programming in Logic),
where the programmer defines relationships and facts, and the system uses logical inference to answer queries
or solve problems. In AI, logic programming is often used to model knowledge and reason about complex
scenarios, enabling machines to solve problems by following a sequence of logical steps. AI and logic
programming are closely linked, as logic forms a foundation for reasoning in AI systems. Logic programming
provides a formal way to express knowledge and enables automated reasoning, which is essential for tasks
such as natural language processing, expert systems, and machine learning. The combination of AI and logic
programming facilitates the development of intelligent systems capable of learning, adapting, and making
decisions autonomously. This book explores the integration of artificial intelligence with logic programming,
emphasizing how logic-based approaches enhance reasoning and problem-solving capabilities in intelligent
systems.
Contents: 1. Intelligent Agents in Artificial Intelligence, 2. Advancement and Transformation of Artificial
Intelligence, 3. Speech Recognition and Natural Language Processing, 4. Mainstream AI Research, 5. Adaptive
Resonance Theory and Neural Network, 6. Logic Programming, 7. Genetic Algorithms, 8. Role of Planning
Techniques, 9. Approximate Reasoning and Fuzzy Logic Programming.
