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A Guided Tour of Artificial Intelligence Research
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume...
Progress in Artificial Intelligence
This book constitutes the refereed proceedings of the 8th Portuguese Conference on Artificial Intelligence, EPIA '97, held in Coimbra, Portugal, in October 1997. The volume presents 24 revised full papers and 9 revised posters selected from 74 submissions from various countries. Also included are two full invited papers and two abstracts of invited talks. The papers are organized in topical sections on automated reasoning and theorem proving; CBR and machine learning; constraints; intelligent tutoring; knowledge representation; multi-agent systems and DAI; nonmonotonic, qualitative and temporal reasoning, and problem solving.
Interstitial Law-Making in Public International Law: A Study of Environmental Impact Assessments
Environmental Impact Assessment (EIA) requirements are quasi-universal. Praised as the core of the international legal response to ensure environmental protection, this procedure is an information tool for better public decision-making, which can contribute to empowering individuals and civic groups. Based on the historical background of the relevant norms and on case studies, Interstitial Law-Making in International Law: A Study of Environmental Impact Assessments verifies whether the role of procedure in secreting substantive law may be fulfilled in the distinctive legal system of public international law, while appraising how EIA requirements have been conceived and implemented as regards encouraging all international actors to behave in an environmentally conscious way, in a world of heterogeneous political regimes. This book is based on the author’s award winning doctoral dissertation which received the Yale Law School’s Ambrose Gherini Prize for best paper in the field of international law (2018).
Handbook of Defeasible Reasoning and Uncertainty Management Systems
Reasoning under uncertainty is always based on a specified language or for malism, including its particular syntax and semantics, but also on its associated inference mechanism. In the present volume of the handbook the last aspect, the algorithmic aspects of uncertainty calculi are presented. Theory has suffi ciently advanced to unfold some generally applicable fundamental structures and methods. On the other hand, particular features of specific formalisms and ap proaches to uncertainty of course still influence strongly the computational meth ods to be used. Both general as well as specific methods are included in this volume. Broadly speaking, symbolic or logical approaches to uncertaint...
Possibility Theory
In the evolution of scientific theories, concern with uncertainty is almost invariably a concomitant of maturation. This is certainly true of the evolution· of physics, economics, operations research, communication sciences, and a host of other fields. And it is true of what has been happening more recently in the area of artificial intelligence, most notably in the development of theories relating to the management of uncertainty in knowledge-based systems. In science, it is traditional to deal with uncertainty through the use of probability theory. In recent years, however, it has become increasingly clear that there are some important facets of uncertainty which do not lend themselves to analysis by classical probability-based methods. One such facet is that of lexical elasticity, which relates to the fuzziness of words in natural languages. As a case in point, even a simple relation X, Y, and Z, expressed as if X is small and Y is very large then between Z is not very small, does not lend itself to a simple interpretation within the framework of probability theory by reason of the lexical elasticity of the predicates small and large.
Advances in Fuzzy Sets, Possibility Theory, and Applications
Since its inception by Professor Lotfi Zadeh about 18 years ago, the theory of fuzzy sets has evolved in many directions, and is finding applications in a wide variety of fields in which the phenomena under study are too complex or too ill-defined to be analyzed by conventional techniques. Thus, by providing a basis for a systematic approach to approximate reasoning and inexact inference, the theory of fuzzy sets may well have a substantial impact on scientific methodology in the years ahead, particularly in the realms of psychology, economics, engineering, law, medicine, decision-analysis, information retrieval, and artificial intelli gence. This volume consists of 24 selected papers invite...
Optimization Models Using Fuzzy Sets and Possibility Theory
Optimization is of central concern to a number of discip lines. Operations Research and Decision Theory are often consi dered to be identical with optimizationo But also in other areas such as engineering design, regional policy, logistics and many others, the search for optimal solutions is one of the prime goals. The methods and models which have been used over the last decades in these areas have primarily been "hard" or "crisp", i. e. the solutions were considered to be either fea sible or unfeasible, either above a certain aspiration level or below. This dichotomous structure of methods very often forced the modeller to approximate real problem situations of the more-or-less type by yes...
New Frontiers in Computational Intelligence and Its Applications
Computational Intelligence is a broad and active research area that is growing rapidly due to the many successful applications of these new techniques in very diverse problems. Many industries have benefited from adopting this technology. The increased number of patents and diverse range of products developed using computational intelligence methods is evidence of this fact. The goal of this book is to provide highlights of the current research in computational intelligence area. The book consists of research papers in the fields of neural networks, fuzzy logic, evolutionary computing, hybrid evolutionary computing-fuzzy logic systems, hybrid neural networks-evolutionary computing and fuzzy logic systems, image processing and vision, advances in robotics, control and manufacturing, and rough sets.
