AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java
| Author | : George F. Luger |
| Publisher | : Addison-Wesley |
| Total Pages | : 0 |
| Release | : 2009 |
| Genre | : Algorithms |
| ISBN | : 9780136070474 |
Ai Algorithms Data Structures And Idioms In Prolog Lisp And Java
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Paradigms of Artificial Intelligence Programming
| Author | : Peter Norvig |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 975 |
| Release | : 2014-06-28 |
| Genre | : Computers |
| ISBN | : 0080571158 |
Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.
Learn Data Structures and Algorithms with Golang
| Author | : Bhagvan Kommadi |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 324 |
| Release | : 2019-03-30 |
| Genre | : Computers |
| ISBN | : 178961841X |
Explore Golang's data structures and algorithms to design, implement, and analyze code in the professional setting Key FeaturesLearn the basics of data structures and algorithms and implement them efficientlyUse data structures such as arrays, stacks, trees, lists and graphs in real-world scenariosCompare the complexity of different algorithms and data structures for improved code performanceBook Description Golang is one of the fastest growing programming languages in the software industry. Its speed, simplicity, and reliability make it the perfect choice for building robust applications. This brings the need to have a solid foundation in data structures and algorithms with Go so as to build scalable applications. Complete with hands-on tutorials, this book will guide you in using the best data structures and algorithms for problem solving. The book begins with an introduction to Go data structures and algorithms. You'll learn how to store data using linked lists, arrays, stacks, and queues. Moving ahead, you'll discover how to implement sorting and searching algorithms, followed by binary search trees. This book will also help you improve the performance of your applications by stringing data types and implementing hash structures in algorithm design. Finally, you'll be able to apply traditional data structures to solve real-world problems. By the end of the book, you'll have become adept at implementing classic data structures and algorithms in Go, propelling you to become a confident Go programmer. What you will learnImprove application performance using the most suitable data structure and algorithmExplore the wide range of classic algorithms such as recursion and hashing algorithmsWork with algorithms such as garbage collection for efficient memory management Analyze the cost and benefit trade-off to identify algorithms and data structures for problem solvingExplore techniques for writing pseudocode algorithm and ace whiteboard coding in interviewsDiscover the pitfalls in selecting data structures and algorithms by predicting their speed and efficiencyWho this book is for This book is for developers who want to understand how to select the best data structures and algorithms that will help solve coding problems. Basic Go programming experience will be an added advantage.
Artificial Intelligence
| Author | : George F. Luger |
| Publisher | : Pearson Higher Ed |
| Total Pages | : 779 |
| Release | : 2011-11-21 |
| Genre | : Computers |
| ISBN | : 0133001733 |
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one- or two-semester undergraduate course on AI. In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence–solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by today’s computer scientists.
Algorithms and Data Structures
| Author | : Kurt Mehlhorn |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 300 |
| Release | : 2008-05-27 |
| Genre | : Computers |
| ISBN | : 3540779787 |
Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.
Hands-On Data Structures and Algorithms with Python
| Author | : Dr. Basant Agarwal |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 389 |
| Release | : 2018-10-31 |
| Genre | : Computers |
| ISBN | : 1788991931 |
Learn to implement complex data structures and algorithms using Python Key FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook Description Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms. What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is for This book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
Knowing our World: An Artificial Intelligence Perspective
| Author | : George F. Luger |
| Publisher | : Springer Nature |
| Total Pages | : 267 |
| Release | : 2021-07-02 |
| Genre | : Computers |
| ISBN | : 3030718735 |
Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind’s history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals. Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building. The book’s second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use. The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.
Programming in Prolog
| Author | : W. F. Clocksin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 292 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642966616 |
The computer programming language Prolog is quickly gaining popularity throughout the world. Since Its beginnings around 1970. Prolog has been chosen by many programmers for applications of symbolic computation. including: D relational databases D mathematical logic D abstract problem solving D understanding natural language D architectural design D symbolic equation solving D biochemical structure analysis D many areas of artificial Intelligence Until now. there has been no textbook with the aim of teaching Prolog as a practical programming language. It Is perhaps a tribute to Prolog that so many people have been motivated to learn It by referring to the necessarily concise reference manuals. a few published papers. and by the orally transmitted 'folklore' of the modern computing community. However. as Prolog is beginning to be Introduced to large numbers of undergraduate and postgraduate students. many of our colleagues have expressed a great need for a tutorial guide to learning Prolog. We hope this little book will go some way towards meeting this need. Many newcomers to Prolog find that the task of writing a Prolog program Is not like specifying an algorithm in the same way as In a conventional programming language. Instead. the Prolog programmer asks more what formal relationships and objects occur In his problem.
Adventure in Prolog
| Author | : Dennis Merritt |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 187 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461234263 |
Not long ago" Dennis Merritt wrote one of the best books that I know of about implementing expert systems in Prolog, and I was very glad he published it in our series. The only problem is there are still some unfortunate people around who do not know Prolog and are not sufficiently prepared either to read Merritt's book, or to use this extremely productive language, be it for knowledge-based work or even for everyday programming. Possibly this last statement may surprise you if you were under the impression that Prolog was an "artificial intelligence language" with very limited application potential. Please believe this editor's statement that quite the opposite is true: for at least four years, I have been using Prolog for every programming task in which I am given the option of choosing the language. Therefore, I 'am indeed happy that Dennis Merritt has written another good book on my language of choice, and that it meets the high standard he set with his prior book, Building Expert Systems in Prolog. All that remains for me to do is to wish you success and enjoyment when taking off on your Adventure in Prolog.
Handbook of Open Source Tools
| Author | : Sandeep Koranne |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 505 |
| Release | : 2010-10-17 |
| Genre | : Computers |
| ISBN | : 1441977198 |
Handbook of Open Source Tools introduces a comprehensive collection of advanced open source tools useful in developing software applications. The book contains information on more than 200 open-source tools which include software construction utilities for compilers, virtual-machines, database, graphics, high-performance computing, OpenGL, geometry, algebra, graph theory , GUIs and more. Special highlights for software construction utilities and application libraries are included. Each tool is covered in the context of a real like application development setting. This unique handbook presents a comprehensive discussion of advanced tools, a valuable asset used by most application developers and programmers; includes a special focus on Mathematical Open Source Software not available in most Open Source Software books, and introduces several tools (eg ACL2, CLIPS, CUDA, and COIN) which are not known outside of select groups, but are very powerful. Handbook of Open Source Tools is designed for application developers and programmers working with Open Source Tools. Advanced-level students concentrating on Engineering, Mathematics and Computer Science will find this reference a valuable asset as well.
