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Common LISP Modules: Artificial Intelligence in the Era of Neural Networks and Chaos Theory 1991st Edition
XCD 178
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This book presents programming techniques which will be useful in both AI projects and more conventional software engineering endeavors.
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| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
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AI Researchers
Ideal for AI researchers seeking insights into LISP programming and its applications in neural networks and chaos theory.
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Students of AI
Beneficial for students studying artificial intelligence, providing foundational knowledge of LISP in advanced topics like neural networks.
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LISP Enthusiasts
Great for LISP programmers wanting to deepen their understanding of AI concepts and how LISP can be applied effectively.
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Beginner Programmers
Not suitable for beginner programmers unfamiliar with programming concepts, as it assumes prior knowledge of LISP and AI.
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Casual Readers
Casual readers may find the technical depth overwhelming and not suited for light or recreational reading.
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Non-Technical Users
Non-technical users may struggle to grasp the complex concepts of AI and neural networks presented in this book.
Product Description
Common LISP Modules: Artificial Intelligence in the Era of Neural Networks and Chaos Theory 1991st Edition
Customer Questions & Answers
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Question:
What is the primary focus of 'Common LISP Modules: Artificial Intelligence in the Era of Neural Networks and Chaos Theory'?
Answer: This book primarily focuses on the intersection of artificial intelligence and advanced mathematical concepts like neural networks and chaos theory, using Common LISP as the programming language. It explores how AI can be enhanced through complex systems theory and neural models, offering insights into real-world applications. The content is essential for students and professionals wanting to understand AI's theoretical foundations while utilizing LISP to prototype solutions. -
Question:
Who is the intended audience for this book?
Answer: The intended audience includes students, researchers, and professionals in computer science and artificial intelligence, particularly those interested in programming with Common LISP. The book aims to provide a deeper understanding of AI methodologies and mathematical theories. Its advanced concepts make it particularly appealing to those already familiar with programming and eager to expand their knowledge in AI development and theoretical applications. -
Question:
How does this book incorporate chaos theory into artificial intelligence?
Answer: The book discusses chaos theory's principles, explaining how they can be applied to enhance AI algorithms. It provides frameworks for understanding complex, dynamic behaviors in AI systems that exhibit unpredictable states. By applying these concepts, developers can improve AI efficiency and adaptability in various applications, such as robotics and predictive modeling, where managing uncertainty is crucial. -
Question:
What programming language does this book primarily focus on and why?
Answer: The primary programming language used in this book is Common LISP, chosen for its versatility in developing AI systems. Common LISP's powerful features, such as dynamic typing and garbage collection, make it well-suited for experimentation with complex AI algorithms. The book provides code examples and modules that readers can directly implement and modify, providing a practical learning experience for those interested in LISP programming. -
Question:
What kind of projects can be developed using the concepts from this book?
Answer: Readers can develop a wide range of AI projects using the principles outlined in this book, including neural network simulations, chaos-based algorithms, and machine learning applications. For example, one could create a self-learning robot using the methods described, or apply chaos theory to predict stock market trends. These projects allow hands-on experience of integrating complex theories into functional AI models. -
Question:
Does this book include practical examples or case studies?
Answer: Yes, the book includes various practical examples and theoretical case studies that demonstrate how to apply AI concepts using Common LISP. It allows readers to see how theoretical knowledge translates into practice, enhancing understanding. Such examples range from basic algorithms to advanced systems, making it suitable for readers with varying levels of expertise in AI and programming. -
Question:
What are the benefits of learning AI through Common LISP as described in the book?
Answer: Learning AI through Common LISP, as outlined in this book, allows readers to leverage its rich set of features tailored for AI development. Common LISP facilitates rapid prototyping and iterative experimentation. By mastering these skills, individuals can efficiently develop innovative AI solutions, making them more competitive in the tech job market and enhancing their research capabilities. This practical focus helps bridge the gap between theory and application. -
Question:
What is the significance of the second printing in 1992 for this book?
Answer: The second printing indicates that the book had sufficient demand to warrant a reprint, reflecting its value to the academic and professional communities in AI and programming. This edition also typically includes corrections and updates based on feedback from readers, ensuring clarity and precision in conveying complicated ideas. Thus, readers can be confident they are using a refined resource that has been validated by its audience. -
Question:
What background knowledge is recommended before reading this book?
Answer: It is recommended that readers have a foundational knowledge of programming concepts and principles, particularly in LISP and general computer science. Familiarity with basic AI concepts and mathematical theories, especially neural networks and chaos theory, can significantly enhance comprehension and engagement. This background will allow readers to fully grasp the complexities and applications discussed throughout the book. -
Question:
Where can I buy 'Common LISP Modules: Artificial Intelligence in the Era of Neural Networks and Chaos Theory' in Grenada?
Answer: You can purchase 'Common LISP Modules: Artificial Intelligence in the Era of Neural Networks and Chaos Theory' from Ubuy, which provides a wide range of options and resources for obtaining this book efficiently. Ubuy is known for its user-friendly interface and reliable service, making it a convenient choice for acquiring specialized books like this one.
Intelligence & Semantics Editorial Review
This book, first published in 1991 and corrected in its second printing in 1992, focuses on Common LISP modules and their application in the field of Artificial Intelligence. It explores how these modules can be used to implement foundational concepts of AI, such as neural networks and chaos theory. The author provides in-depth explanations and examples, making it accessible to both beginners and experienced programmers. This book is a valuable resource for anyone interested in AI and LISP programming.
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Pros
- Provides a detailed understanding of Common LISP modules
- Explains the application of LISP in Artificial Intelligence
- Covers foundational concepts like neural networks and chaos theory
- Suitable for both beginners and experienced programmers
Product Price History
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XCD 178
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Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.
Features & Benefits
- Offers essential programming techniques for AI and software engineering.
- Focuses on creativity and practical experience in problem-solving.
- Includes reusable software modules for diverse programming needs.
- Presents challenging example applications to foster learning.
- Designed to both entertain and educate programmers.
- Includes a portable graphics library for enhanced application compatibility.