This book is concerned with the rich and fruitful interplay between the fields of computational logic and machine learning. The intended audience is senior undergraduates, graduate students, and researchers in either of those fields. For those in computational logic, no previous knowledge of machine learning is assumed, and for those in machine learning no previous knowledge of computational logic is assumed.The logic used throughout the book is a higher-order one, since higher-order functions can have other functions as arguments and this capability can be exploited to provide abstractions for knowledge representation, methods for constructing predicates, and a foundation for logic-based computation. The book should be of interest to researchers in machine learning, especially those who study learning methods for structured data. Throughout, great emphasis is placed on learning comprehensible theories. The book serves as an introduction for computational logicians to machine learning, a particularly interesting and important application area of logic, and also provides a foundation for functional logic programming languages.

Enduring Issues in Special Education is aimed at any course in the undergraduate or graduate special education curriculum that is wholly or partly devoted to a critical examination of current issues in special education. The book organizes 28 chapters into seven sections using familiar structuring principles-what, who, where, how, when, why, and whither. Each section begins with an introduction that provides historical, legal, and theoretical background information and organizing commentary for the chapters that follow. The book's objective, in addition to informing readers about the issues, is to develop critical thinking skills in the context of special education. Key features include the following: Dialectic Format - Each of the 28 chapters presents compelling reasons for addressing the issue at hand and specific ways to do so. Because each issue is written from different perspectives and focuses on a variety of aspects, readers are encouraged to weigh the arguments, seek additional information, and come up with synthesized positions of their own. Organizing Framework - The book's seven sections have been arranged according to a scheme that is the essence of most investigative reporting and provides a coherent, easy-to-understand framework for readers. Expertise - All chapters are written by leading scholars who are highly regarded experts in their fields and conclude with suggested readings and discussion questions for additional study.

Enduring Issues in Special Education is aimed at any course in the undergraduate or graduate special education curriculum that is wholly or partly devoted to a critical examination of current issues in special education. The book organizes 28 chapters into seven sections using familiar structuring principles-what, who, where, how, when, why, and whither. Each section begins with an introduction that provides historical, legal, and theoretical background information and organizing commentary for the chapters that follow. The book's objective, in addition to informing readers about the issues, is to develop critical thinking skills in the context of special education. Key features include the following: Dialectic Format - Each of the 28 chapters presents compelling reasons for addressing the issue at hand and specific ways to do so. Because each issue is written from different perspectives and focuses on a variety of aspects, readers are encouraged to weigh the arguments, seek additional information, and come up with synthesized positions of their own. Organizing Framework - The book's seven sections have been arranged according to a scheme that is the essence of most investigative reporting and provides a coherent, easy-to-understand framework for readers. Expertise - All chapters are written by leading scholars who are highly regarded experts in their fields and conclude with suggested readings and discussion questions for additional study.

In the two and a half years since the frrst edition of this book was published, the field of logic programming has grown rapidly. Consequently, it seemed advisable to try to expand the subject matter covered in the first edition. The new material in the second edition has a strong database flavour, which reflects my own research interests over the last three years. However, despite the fact that the second edition has about 70% more material than the first edition, many worthwhile topic!! are still missing. I can only plead that the field is now too big to expect one author to cover everything. In the second edition, I discuss a larger class of programs than that discussed in the first edition. Related to this, I have also taken the opportunity to try to improve some of the earlier terminology. Firstly, I introduce "program statements", which are formulas of the form A+-W, where the head A is an atom and the body W is an arbitrary formula. A "program" is a finite set of program statements. There are various restrictions of this class. "Normal" programs are ones where the body of each program statement is a conjunction of literals. (The terminology "general", used in the first edition, is obviously now inappropriate).

This book provides a systematic approach to knowledge representation, computation, and learning using higher-order logic. For those interested in computational logic, it provides a framework for knowledge representation and computation based on higher-order logic, and demonstrates its advantages over more standard approaches based on first-order logic. For those interested in machine learning, the book explains how higher-order logic provides suitable knowledge representation formalisms and hypothesis languages for machine learning applications.