Rlisp '88: An Evolutionary Approach To Program Design And Reuse


Book Description

The RLISP '88 programming system introduces an evolutionary approach to software development that enables small groups of programmers to advance the state of the art over a period of many years. Each new system is built on top of the old; yet, like an Irishman's hammer, little remains of the original program code. This book presents a style of durable programming for domain specialists and computer scientists alike. Exercises at the end of each chapter encourage its use as a textbook.




New Approaches to Knowledge Acquisition


Book Description

It is well recognized that knowledge acquisition is the critical bottleneck of knowledge engineering. This book presents three major approaches of current research in this field, namely the psychological approach, the artificial intelligence approach and the software engineering approach. Special attention is paid to the most recent advances in knowledge acquisition research, especially those made by Chinese computer scientists. A special chapter is devoted to its applications in other fields, e.g. language analysis, software engineering, computer-aided instruction, etc., which were done in China.




Distributed Constraint Logic Programming


Book Description

This book presents the first attempt to combine concurrent logic programming and constraint logic programing. It is divided into three parts. In the first part, a novel computation model, called the multi-Pandora model, which is designed on the basis of the Pandora model, is presented. In the second part, the distributed implementation schemes for Parlog, Pandora, and multi-Pandora are presented. Finally, the author presents the distributed constraint solvers for finite domain constraints, as well as the distributed constraint solvers in the domains of real numbers and Boolean rings which can be incorporated into the schemes presented in the second part to handle the ?ask?- and ?tell?-constraints.




The Symbolic Computation of Integrability Structures for Partial Differential Equations


Book Description

This is the first book devoted to the task of computing integrability structures by computer. The symbolic computation of integrability operator is a computationally hard problem and the book covers a huge number of situations through tutorials. The mathematical part of the book is a new approach to integrability structures that allows to treat all of them in a unified way. The software is an official package of Reduce. Reduce is free software, so everybody can download it and make experiments using the programs available at our website.




Mathematical Logic for Computer Science


Book Description

Mathematical logic is essentially related to computer science. This book describes the aspects of mathematical logic that are closely related to each other, including classical logic, constructive logic, and modal logic. This book is intended to attend to both the peculiarities of logical systems and the requirements of computer science.In this edition, the revisions essentially involve rewriting the proofs, increasing the explanations, and adopting new terms and notations.




Mathematical Logic For Computer Science (2nd Edition)


Book Description

Mathematical logic is essentially related to computer science. This book describes the aspects of mathematical logic that are closely related to each other, including classical logic, constructive logic, and modal logic. This book is intended to attend to both the peculiarities of logical systems and the requirements of computer science.In this edition, the revisions essentially involve rewriting the proofs, increasing the explanations, and adopting new terms and notations.




Cooperation In Industrial Muti-agent Systems


Book Description

Distributed Artificial Intelligence (DAI) is a vibrant sub-field of Artificial Intelligence concerned with coordinating the knowledge and actions of multiple interacting agents. Although DAI has the potential to overcome many of the problems currently associated with constructing software systems which are large, complex and knowledge rich, there have, as yet, been relatively few attempts to apply it to real world applications. To help pave the way for such future developments, this book recounts the insights gained and the breakthroughs made, whilst building multiple agent systems in the domains of electricity transportation management and control of a particle accelerator. These experiences cover the complete development lifecycle of multi-agent systems for industrial applications: ranging from the initial design, through the implementation, to the testing and evaluation phases. The book's other main features are that it: provides a thorough and up-to-date explanation of the foundation concepts of DAI, describes a new paradigm for building multi-agent systems which uses the concept of reusable cooperation knowledge and develops a new model of cooperation based on the notion of joint intentions.




Cooperation in Industrial Multi-agent Systems


Book Description

Assuming no prior knowledge of Distributed Artificial Intelligence (DAI), this book deals with the complete development lifecycle of multi-agent systems for industrial applications.




Stochastic Complexity In Statistical Inquiry


Book Description

This book describes how model selection and statistical inference can be founded on the shortest code length for the observed data, called the stochastic complexity. This generalization of the algorithmic complexity not only offers an objective view of statistics, where no prejudiced assumptions of 'true' data generating distributions are needed, but it also in one stroke leads to calculable expressions in a range of situations of practical interest and links very closely with mainstream statistical theory. The search for the smallest stochastic complexity extends the classical maximum likelihood technique to a new global one, in which models can be compared regardless of their numbers of parameters. The result is a natural and far reaching extension of the traditional theory of estimation, where the Fisher information is replaced by the stochastic complexity and the Cramer-Rao inequality by an extension of the Shannon-Kullback inequality. Ideas are illustrated with applications from parametric and non-parametric regression, density and spectrum estimation, time series, hypothesis testing, contingency tables, and data compression.