Many-valued logics were developed as an attempt to handle philosophical doubts about the "law of excluded middle" in classical logic. The first many-valued formal systems were developed by J. Lukasiewicz in Poland and E.Post in the U.S.A. in the 1920s, and since then the field has expanded dramatically as the applicability of the systems to other philosophical and semantic problems was recognized. Intuitionisticlogic, for example, arose from deep problems in the foundations of mathematics. Fuzzy logics, approximation logics, and probability logics all address questions that classical logic alone cannot answer. All these interpretations of many-valued calculi motivate specific formal systems thatallow detailed mathematical treatment. In this volume, the authors are concerned with finite-valued logics, and especially with three-valued logical calculi. Matrix constructions, axiomatizations of propositional and predicate calculi, syntax, semantic structures, and methodology are discussed. Separate chapters deal with intuitionistic logic, fuzzy logics, approximation logics, and probability logics. These systems all find application in practice, in automatic inference processes, which have been decisive for the intensive development of these logics. This volume acquaints the reader with theoretical fundamentals of many-valued logics. It is intended to be the first of a two-volume work. The second volume will deal with practical applications and methods of automated reasoning using many-valued logics.

Many-valued logics is becoming increasingly important in many branches of science. This is the second volume of a comprehensive two-volume handbook on many-valued logics by two leading members of the famous Polish school of logic. While the first volume of 1992 was mainly concerned with theoretical foundations, this volume emphasizes automated reasoning, practical applications, and latest developments in closely related fields, such as fuzzy logics and rough set theory. It offers an extensive overview of Gentzen deduction systems and multi-sequential systems in many-valued logics and shows the application of the resolution principle to this logics. It discusses applications in such areas as software specification and electronic circuit verification and presents fuzzy logics and rough set theory in detail.

Originally published in 1995 Time and Logic examines understanding and application of temporal logic, presented in computational terms. The emphasis in the book is on presenting a broad range of approaches to computational applications. The techniques used will also be applicable in many cases to formalisms beyond temporal logic alone, and it is hoped that adaptation to many different logics of program will be facilitated. Throughout, the authors have kept implementation-orientated solutions in mind. The book begins with an introduction to the basic ideas of temporal logic. Successive chapters examine particular aspects of the temporal theoretical computing domain, relating their applications to familiar areas of research, such as stochastic process theory, automata theory, established proof systems, model checking, relational logic and classical predicate logic. This is an essential addition to the library of all theoretical computer scientists. It is an authoritative work which will meet the needs both of those familiar with the field and newcomers to it.

This book constitutes the refereed proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2012, held in Warsaw, Poland, in September 2012. The 89 revised full papers presented were carefully reviewed and selected from various submissions. The papers are organized in topical sections on computer graphics, computer vision and visual surveillance.

Augmented Transition Network Grammars are at present the most widely used method for analyzing natural languages. Despite the increasing po pularity of this method, however, no extensive papers on ATN-Grammars have been presented which would be accessible to a larger number of per sons engaged in the problem from both the theoretical and practical points of view. Augmented Transition Networks (ATN) are derived from state automata. Like a finite state automaton, an ATN consists of a collection of la beled states and arcs, a distinguished start state and a set of distin guished final states. States are connected with each other by arcs crea ting a directed graph or net. The label on an arc indicates a terminal symbol (word) or the type of words which must occur in an input stream to allow the transition to the next state. It is said that a sequence of words (or sentence) is accepted by such a net if there exists a se quence of arcs (usually called a path), connecting the start state with a final state, which can be followed to the sentence. The finite state automaton is then enriched by several facilities which increase its computational power. The most important of them permits some arcs to be labeled by nonterminal rather than terminal symbols. This means that the transition through such an arc is actually the re cursive application of the net beginning with a pointed state."

In recent years, machine learning has emerged as a significant area of research in artificial intelligence and cognitive science. At present, research in the field is being intensified from both the point of view of theory and of implementation, and the results are being introduced in practice. Machine learning has recently become the subject of interest of many young and talented scientists whose bold ideas have greatly contributed to the broadening of knowledge in this rapidly developing field of science. This situation has manifested itself in an increasing number of valuable contributions to scientific journals. However, such papers are necessarily compact descriptions of research problems. "Computational Models of Learning" supplements these contributions and is a collection of more extensive essays. These essays provide the reader with an increased knowledge of carefully selected problems of machine learning.

Up to now there has been no scientific publication on natural lan guage research that presents a broad and complex description of the current problems of parsing in the context of Artificial Intelli gence. However, there are many interesting results from this domain appearing mainly in numerous articles published in pro fessional journals. In view of this situation, the objective of this book is to enable scientists from different countries to present the results of their research on natural language parsing in the form of more detailed papers than would be possible in professional jour nals. This book thus provides a collection of studies written by well known scientists whose earlier publications have greatly contributed to the development of research on natural language parsing. Jaime G. Carbonell and Philip J. Hayes present in their paper "Robust Parsing Using Multiple Construction-Specific Strategies" two small experimental parsers, implemented to illustrate the advantages of a multi-strategy approach to parsers, with strategies selected according to the type of construction being parsed at any given time. This presentation is followed by the description of a parsing algorithm, integrating some of the best features of the two smaller parsers, including case-frame instantiation and partial pat tern-matching strategies."

Information systems are large repositories of factual and inferential knowledge intended to be queried and maintained by a wide variety of users with different backgrounds and work tasks. The community of potential information system users is growing rapidly with advances in hardware and software technology that permit computer/communications support for more and more application areas. Unfortunately, it is often felt that progress in user interface technology has not quite matched that of other areas. Technical solutions such as computer graphics, natural language processing, or man-machine-man communications in office systems are not enough by themselves. They should be complemented by system features that ensure cooperative behavior of the interfaces, thus reducing the training and usage effort required for successful interaction. In analogy to a human dialog partner, we call an interface cooperative if it does not just accept user requests passively or answer them literally, but actively attempts to understand the users' intentions and to help them solve their applica tion problems. This leads to the central question addressed by this book: What makes an information systems interface cooperative, and how do we provide capabilities leading to cooperative interfaces? Many answers are possible. A first aspect concerns the formulation and accep tance of user requests. Many researchers assume that such requests should be formulated in natural language."

This book contains the reports of selected projects involving natural language commu nication with pictorial information systems. More than just a record of research results, however, it presents concrete applications to the solution of a wide variety of problems. The authors are all prominent figures in the field whose authoritative contributions help ensure its continued expansion in both size and significance. Y. C. Lee and K S. Fu (Purdue University, USA) survey picture query languages which form an interface between the pictorial database system and the user and support infor mation retrieval, data entry and manipulation, data analysis and output generation. They include explicit picture query languages that augment alphanumeric data query langua ges as well as languages and command sets which are implicitly embedded in a pictorial information system but perform similar functions. It is worth mentioning that some forms of query languages can be transformed from a given set of natural language senten ces by using ATN (Augmented Transition Networks), which consequently allows for na turallanguage communication with information system."

While expert systems technology originated in the United States, its development has become an international concern. Since the start of the DENDRAL project at Stanford University over 15 years ago, with its objective of problem-solving via the automation of actual human expert knowledge, significant expert systems projects have been completed in countries rang ing from Japan to France, Spain to China. This book presents a sample of five such projects, along with four substantial reports of mature studies from North American researchers. Two important issues of expert system design permeate the papers in this volume. The first concerns the incorporation of substantial numeric knowledge into a system. This has become a significant focus of work as researchers have sought to apply expert systems tech nology to complex, real-world domains already subject to statistical or algebraic description (and handled well at some level in numeric terms). A second prominent issue is that of representing control knowledge in a manner which is both explicit, and thus available for inspection, and compatible with the semantics of the problem domain."

Natural language generation is a field within artificial intelligence which looks ahead to the future when machines will communicate complex thoughts to their human users in a natural way. Generation systems supply the sophisticated knowledge about natural languages that must come into play when one needs to use wordings that will overpower techniques based only on symbolic string manipulation techniques. Topics covered in this volume include discourse theory, mechanical translation, deliberate writing, and revision. "Natural Language Generation Systems" contains contributions by leading researchers in the field. Chapters contain details of grammatical treatments and processing seldom reported on outside of full length monographs.

Many-valued logics were developed as an attempt to handle philosophical doubts about the "law of excluded middle" in classical logic. The first many-valued formal systems were developed by J. Lukasiewicz in Poland and E.Post in the U.S.A. in the 1920s, and since then the field has expanded dramatically as the applicability of the systems to other philosophical and semantic problems was recognized. Intuitionisticlogic, for example, arose from deep problems in the foundations of mathematics. Fuzzy logics, approximation logics, and probability logics all address questions that classical logic alone cannot answer. All these interpretations of many-valued calculi motivate specific formal systems thatallow detailed mathematical treatment. In this volume, the authors are concerned with finite-valued logics, and especially with three-valued logical calculi. Matrix constructions, axiomatizations of propositional and predicate calculi, syntax, semantic structures, and methodology are discussed. Separate chapters deal with intuitionistic logic, fuzzy logics, approximation logics, and probability logics. These systems all find application in practice, in automatic inference processes, which have been decisive for the intensive development of these logics. This volume acquaints the reader with theoretical fundamentals of many-valued logics. It is intended to be the first of a two-volume work. The second volume will deal with practical applications and methods of automated reasoning using many-valued logics.

Many-valued logics are becoming increasingly important in all areas of computer science. This is the second volume of an authoritative two-volume handbook on many valued logics by two leading figures in the field. While the first volume was mainly concerned with theoretical foundations, this volume emphasizes automated reasoning, practical applications, and the latest developments in fuzzy logic and rough set theory. Among the applications presented are those in software specification and electronic circuit verification.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2008, held in Warsaw, Poland, in November 2008.

The 48 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on image processing, image quality assessment, geometrical models of objects and scenes, motion analysis, visual navigation and active vision, image and video coding, virtual reality and multimedia applications, biomedical applications, practical applications of pattern recognition, computer animation, visualization and graphical data presentation.

The 2nd Workshop on Intelligent Media Technology for Communicative Intelligence commemorating the 10th anniversary of the Polish-Japanese Institute of Information Technology in Warsaw aimed to explore the current research topics in the ?eld of int- ligent media technologies for communicative intelligence. Communicative intelligence represents a new challenge towards building a sup- intelligence on the ubiquitous global network by accumulating a huge amount of - man andknowledgeresources.The term "communicativeintelligence"re?ects the view that communication is at the very core of intelligence and its creation. Communication permits novel ideas to emerge from intimate interactions by multiple agents, ranging from collaboration to competition. The recent advance of information and commu- cation technologies has established an information infrastructure that allows humans and artifacts to communicate with each other beyond space and time. It enables us to advance a step further to realize a communicative intelligence with many fruitful applications. Intelligentmediatechnologiesattempttocaptureandaugmentpeople'scommuni- tive activities by embedding computers into the environment to enhance interactions in an unobtrusive manner. The introduction of embodied conversational agents that might mediate conversations among people in a social context is the next step in the p- cess. The scope of intelligent media technologies includes design and development of intelligent supports for content production, distribution, and utilization, since rich c- tent is crucial for communication in many applications. The promising applications of intelligence media technologies include e-learning, knowledge management systems, e-democracy, and other communication-intensivesubject domains.