Get started with the simplest, most powerful prolog ever: Visual Prolog If you want to explore the potential of Artificial Intelligence (AI), you need to know your way around Prolog. Prolog - which stands for "programming with logic" - is one of the most effective languages for building AI applications, thanks to its unique approach. Rather than writing a program that spells out exactly how to solve a problem, with Prolog you define a problem with logical Rules, and then set the computer loose on it. This paradigm shift from Procedural to Declarative programming makes Prolog ideal for applications involving AI, logic, language parsing, computational linguistics, and theorem-proving. Now, Visual Prolog (available as a free download) offers even more with its powerful Graphical User Interface (GUI), built-in Predicates, and rather large provided Program Foundation Class (PFC) libraries. A Guide to Artificial Intelligence with Visual Prolog is an excellent introduction to both Prolog and Visual Prolog. Designed for newcomers to Prolog with some conventional programming background (such as BASIC, C, C++, Pascal, etc.), Randall Scott proceeds along a logical, easy-to-grasp path as he explains the beginnings of Prolog, classic algorithms to get you started, and many of the unique features of Visual Prolog. Readers will also gain key insights into application development, application design, interface construction, troubleshooting, and more. In addition, there are numerous sample examples to learn from, copious illustrations and information on helpful resources. A Guide to Artificial Intelligence with Visual Prolog is less like a traditional textbook and more like a workshop where you can learn at your own pace - so you can start harnessing the power of Visual Prolog for whatever your mind can dream up.

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.

The emphasis in The Craft of Prolog is on using Prolog effectively. It presents a loose collection of topics that build on and elaborate concepts learned in a first course. Hacking your program is no substitute for understanding your problem. Prolog is different, but not that different. Elegance is not optional. These are the themes that unify Richard O'Keefe's very personal statement on how Prolog programs should be written. The emphasis in The Craft of Prolog is on using Prolog effectively. It presents a loose collection of topics that build on and elaborate concepts learned in a first course. These may be read in any order following the first chapter, "Basic Topics in Prolog," which provides a basis for the rest of the material in the book. Richard A. O'Keefe is Lecturer in the Department of Computer Science at the Royal Melbourne Institute of Technology. He is also a consultant to Quintus Computer Systems, Inc.Contents: Basic Topics in Prolog. Searching. Where Does the Space Go? Methods of Programming. Data Structure Design. Sequences. Writing Interpreters. Some Notes on Grammar Rules. Prolog Macros. Writing Tokenisers in Prolog. All Solutions.

This book is for people who have done some programming, either in Prolog or in a language other than Prolog, and who can find their way around a reference manual. The emphasis of this book is on a simplified and disciplined methodology for discerning the mathematical structures related to a problem, and then turning these structures into Prolog programs. This book is therefore not concerned about the particular features of the language nor about Prolog programming skills or techniques in general. A relatively pure subset of Prolog is used, which includes the 'cut', but no input/output, no assert/retract, no syntactic extensions such as if then-else and grammar rules, and hardly any built-in predicates apart from arithmetic operations. I trust that practitioners of Prolog program ming who have a particular interest in the finer details of syntactic style and language features will understand my purposes in not discussing these matters. The presentation, which I believe is novel for a Prolog programming text, is in terms of an outline of basic concepts interleaved with worksheets. The idea is that worksheets are rather like musical exercises. Carefully graduated in scope, each worksheet introduces only a limited number of new ideas, and gives some guidance for practising them. The principles introduced in the worksheets are then applied to extended examples in the form of case studies.

Written for those who wish to learn Prolog as a powerful software development tool, but do not necessarily have any background in logic or AI. Includes a full glossary of the technical terms and self-assessment exercises.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author’s website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.

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.

Constraint logic programming lies at the intersection of logic programming, optimisation and artificial intelligence. It has proved a successful tool in many areas including production planning, transportation scheduling, numerical analysis and bioinformatics. Eclipse is one of the leading software systems that realise its underlying methodology. Eclipse is exploited commercially by Cisco, and is freely available and used for teaching and research in over 500 universities. This book has a two-fold purpose. It's an introduction to constraint programming, appropriate for one-semester courses for upper undergraduate or graduate students in computer science or for programmers wishing to master the practical aspects of constraint programming. By the end of the book, the reader will be able to understand and write constraint programs that solve complex problems. Second, it provides a systematic introduction to the Eclipse system through carefully-chosen examples that guide the reader through the language and illustrate its power, versatility and utility.