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General game players are computer systems able to play strategy
games based solely on formal game descriptions supplied at
"runtime" (n other words, they don't know the rules until the game
starts). Unlike specialized game players, such as Deep Blue,
general game players cannot rely on algorithms designed in advance
for specific games; they must discover such algorithms themselves.
General game playing expertise depends on intelligence on the part
of the game player and not just intelligence of the programmer of
the game player. GGP is an interesting application in its own
right. It is intellectually engaging and more than a little fun.
But it is much more than that. It provides a theoretical framework
for modeling discrete dynamic systems and defining rationality in a
way that takes into account problem representation and complexities
like incompleteness of information and resource bounds. It has
practical applications in areas where these features are important,
e.g., in business and law. More fundamentally, it raises questions
about the nature of intelligence and serves as a laboratory in
which to evaluate competing approaches to artificial intelligence.
This book is an elementary introduction to General Game Playing
(GGP). (1) It presents the theory of General Game Playing and
leading GGP technologies. (2) It shows how to create GGP programs
capable of competing against other programs and humans. (3) It
offers a glimpse of some of the real-world applications of General
Game Playing.
Data integration is a critical problem in our increasingly
interconnected but inevitably heterogeneous world. There are
numerous data sources available in organizational databases and on
public information systems like the World Wide Web. Not
surprisingly, the sources often use different vocabularies and
different data structures, being created, as they are, by different
people, at different times, for different purposes. The goal of
data integration is to provide programmatic and human users with
integrated access to multiple, heterogeneous data sources, giving
each user the illusion of a single, homogeneous database designed
for his or her specific need. The good news is that, in many cases,
the data integration process can be automated. This book is an
introduction to the problem of data integration and a rigorous
account of one of the leading approaches to solving this problem,
viz., the relational logic approach. Relational logic provides a
theoretical framework for discussing data integration. Moreover, in
many important cases, it provides algorithms for solving the
problem in a computationally practical way. In many respects,
relational logic does for data integration what relational algebra
did for database theory several decades ago. A companion web site
provides interactive demonstrations of the algorithms. Table of
Contents: Preface / Interactive Edition / Introduction / Basic
Concepts / Query Folding / Query Planning / Master Schema
Management / Appendix / References / Index / Author Biography Don't
have access? Recommend our Synthesis Digital Library to your
library or purchase a personal subscription. Email
[email protected] for details.
Logic Programming is a style of programming in which programs take
the form of sets of sentences in the language of Symbolic Logic.
Over the years, there has been growing interest in Logic
Programming due to applications in deductive databases, automated
worksheets, Enterprise Management (business rules), Computational
Law, and General Game Playing. This book introduces Logic
Programming theory, current technology, and popular applications.
In this volume, we take an innovative, model-theoretic approach to
logic programming. We begin with the fundamental notion of
datasets, i.e., sets of ground atoms. Given this fundamental
notion, we introduce views, i.e., virtual relations; and we define
classical logic programs as sets of view definitions, written using
traditional Prolog-like notation but with semantics given in terms
of datasets rather than implementation. We then introduce actions,
i.e., additions and deletions of ground atoms; and we define
dynamic logic programs as sets of action definitions. In addition
to the printed book, there is an online version of the text with an
interpreter and a compiler for the language used in the text and an
integrated development environment for use in developing and
deploying practical logic programs.
This book is a gentle but rigorous introduction to Formal Logic. It
is intended primarily for use at the college level. However, it can
also be used for advanced secondary school students, and it can be
used at the start of graduate school for those who have not yet
seen the material. The approach to teaching logic used here emerged
from more than 20 years of teaching logic to students at Stanford
University and from teaching logic to tens of thousands of others
via online courses on the World Wide Web. The approach differs from
that taken by other books in logic in two essential ways, one
having to do with content, the other with form. Like many other
books on logic, this one covers logical syntax and semantics and
proof theory plus induction. However, unlike other books, this book
begins with Herbrand semantics rather than the more traditional
Tarskian semantics. This approach makes the material considerably
easier for students to understand and leaves them with a deeper
understanding of what logic is all about. In addition to this text,
there are online exercises (with automated grading), online logic
tools and applications, online videos of lectures, and an online
forum for discussion. They are available at
http://intrologic.stanford.edu/
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