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Showing 1 - 25 of 126 matches in All Departments
The domain of nonlinear dynamical systems and its mathematical
underpinnings has been developing exponentially for a century, the
last 35 years seeing an outpouring of new ideas and applications
and a concomitant confluence with ideas of complex systems and
their applications from irreversible thermodynamics. A few examples
are in meteorology, ecological dynamics, andsocial and economic
dynamics. These new ideas have profound implications for our
understanding and practice in domains involving complexity,
predictability and determinism, equilibrium, control, planning,
individuality, responsibility and so on. -Comprehensive coverage of all main theories in the philosophy of Complex Systems -Clearly written expositions of fundamental ideas and concepts -Definitive discussions by leading researchers in the field -Summaries of leading-edge research in related fields are also included"
This collection represents the primary reference work for
researchers and students in the area of Temporal Reasoning in
Artificial Intelligence. Temporal reasoning has a vital role to
play in many areas, particularly Artificial Intelligence. Yet,
until now, there has been no single volume collecting together the
breadth of work in this area. This collection brings together the
leading researchers in a range of relevant areas and provides an
coherent description of the breadth of activity concerning temporal
reasoning in the filed of Artificial Intelligence.
The present work is a continuation of the authors' acclaimed
multi-volume A
- The most extensive coverage compared to competitive works. - Demonstrates not only that abduction is a form of ignorance
preserving - Demonstrates the satisficing rather than maximizing character
of - The development of formal models of abduction is considerably
more extensive than one finds in existing literature. It is an
especially impressive amalgam of sophisticated
Agenda Relevance is the first volume in the authors' omnibus
investigation of
"
Since its inception in the famous 1936 paper by Birkhoff and von
Neumann entitled "The logic of quantum mechanics" quantum logic,
i.e. the logical investigation of quantum mechanics, has undergone
an enormous development. Various schools of thought and approaches
have emerged and there are a variety of technical results.
Greek, Indian and Arabic Logic marks the initial appearance of the
multi-volume Handbook of the History of Logic. Additional volumes
will be published when ready, rather than in strict chronological
order. Soon to appear are The Rise of Modern Logic: From Leibniz to
Frege. Also in preparation are Logic From Russell to Godel, The
Emergence of Classical Logic, Logic and the Modalities in the
Twentieth Century, and The Many-Valued and Non-Monotonic Turn in
Logic. Further volumes will follow, including Mediaeval and
Renaissance Logic and Logic: A History of its Central.
Scientists use concepts and principles that are partly specific for
their subject matter, but they also share part of them with
colleagues working in different fields. Compare the biological
notion of a 'natural kind' with the general notion of
'confirmation' of a hypothesis by certain evidence. Or compare the
physical principle of the 'conservation of energy' and the general
principle of 'the unity of science'. Scientists agree that all such
notions and principles aren't as crystal clear as one might wish.
Legal theory, political sciences, sociology, philosophy, logic, artificial intelligence: there are many approaches to legal argumentation. Each of them provides specific insights into highly complex phenomena. Different disciplines, but also different traditions in disciplines (e.g. analytical and continental traditions in philosophy) find here a rare occasion to meet. The present book contains contributions, both historical and thematic, from leading researchers in several of the most important approaches to legal rationality. One of the main issues is the relation between logic and law: the way logic is actually used in law, but also the way logic can make law explicit. An outstanding group of philosophers, logicians and jurists try to meet this issue. The book is more than a collection of papers. However different their respective conceptual tools may be, the authors share a common conception: legal argumentation is a specific argumentation context.
Lambda Calculi: A Guide Interpolation and Definability Discourse Representation Theory
Philosophy of Biology is a rapidly expanding field. It is concerned
with explanatory concepts in evolution, genetics, and ecology. This
collection of 25 essays by leading researchers provides an overview
of the state of the field. These essays are wholly new; none of
them could have been written even ten years ago. They demonstrate
how philosophical analysis has been able to contribute to sometimes
contested areas of scientific theory making.
This text centers around three main subjects. The first is the concept of modularity and independence in classical logic and nonmonotonic and other nonclassical logic, and the consequences on syntactic and semantical interpolation and language change. In particular, we will show the connection between interpolation for nonmonotonic logic and manipulation of an abstract notion of size. Modularity is essentially the ability to put partial results achieved independently together for a global result. The second aspect of the book is the authors' uniform picture of conditionals, including many-valued logics and structures on the language elements themselves and on the truth value set. The third topic explained by the authors is neighbourhood semantics, their connection to independence, and their common points and differences for various logics, e.g., for defaults and deontic logic, for the limit version of preferential logics, and for general approximation. The book will be of value to researchers and graduate students in logic and theoretical computer science.
Starting with simple examples showing the relevance of cutting and pasting logics, the monograph develops a mathematical theory of combining and decomposing logics, ranging from propositional and first-order based logics to higher-order based logics as well as to non-truth functional logics. The theory covers mechanisms for combining semantic structures and deductive systems either of the same or different nature. The issue of preservation of properties is addressed.
This is an overview of the current state of knowledge along with open problems and perspectives, clarified in such fields as non-standard inferences in description logics, logic of provability, logical dynamics and computability theory. The book includes contributions concerning the role of logic today, including unexpected aspects of contemporary logic and the application of logic. This book will be of interest to logicians and mathematicians in general.
It is with great pleasure that we are presenting to the community the second edition of this extraordinary handbook. It has been over 15 years since the publication of the first edition and there have been great changes in the landscape of philosophical logic since then. The first edition has proved invaluable to generations of students and researchers in formal philosophy and language, as well as to consumers of logic in many applied areas. The main logic article in the Encyclopaedia Britannica 1999 has described the first edition as 'the best starting point for exploring any of the topics in logic'. We are confident that the second edition will prove to be just as good! The first edition was the second handbook published for the logic com- nity. It followed the North Holland one volume Handbook of Mathematical Logic, published in 1977, edited by the late Jon Barwise. The four volume Handbook of Philosophical Logic, published 1983-1989 came at a fortunate temporal junction at the evolution of logic. This was the time when logic was gaining ground in computer science and artificial intelligence circles. These areas were under increasing commercial pressure to provide devices which help and/or replace the human in his daily activity. This pressure required the use of logic in the modelling of human activity and organi- tion on the one hand and to provide the theoretical basis for the computer program constructs on the other.
Psychology is the study of thinking, and cognitive science is the
interdisciplinary investigation of mind and intelligence that also
includes philosophy, artificial intelligence, neuroscience,
linguistics, and anthropology. In these investigations, many
philosophical issues arise concerning methods and central concepts.
such questions for centuries (unrestricted by the capabilities of any hard ware). The principles governing the interaction of several processes, for example, are abstract an similar to principles governing the cooperation of two large organisation. A detailed rule based effective but rigid bureaucracy is very much similar to a complex computer program handling and manipulating data. My guess is that the principles underlying one are very much the same as those underlying the other. I believe the day is not far away in the future when the computer scientist will wake up one morning with the realisation that he is actually a kind of formal philosopher The projected number of volumes for this Handbook is about 18. The subject has evolved and its areas have become interrelated to such an extent that it no longer makes sense to dedicate volumes to topics. However, the volumes do follow some natural groupings of chapters. I would like to thank our authors are readers for their contributions and their commitment in making this Handbook a success. Thanks also to our publication administrator Mrs J. Spurr for her usual dedication and excellence and to Kluwer Academic Publishers for their continuing support for the Handbook."
It is with great pleasure that we are presenting to the community the second edition of this extraordinary handbook. It has been over 15 years since the publication of the first edition and there have been great changes in the landscape of philosophical logic since then. The first edition has proved invaluable to generations of students and researchers in formal philosophy and language, as well as to consumers of logic in many applied areas. The main logic article in the Encyclopaedia Britannica 1999 has described the first edition as 'the best starting point for exploring any of the topics in logic'. We are confident that the second edition will prove to be just as good The first edition was the second handbook published for the logic commu nity. It followed the North Holland one volume Handbook of Mathematical Logic, published in 1977, edited by the late Jon Barwise. The four volume Handbook of Philosophical Logic, published 1983-1989 came at a fortunate temporal junction at the evolution of logic. This was the time when logic was gaining ground in computer science and artificial intelligence circles. These areas were under increasing commercial pressure to provide devices which help and/or replace the human in his daily activity. This pressure required the use of logic in the modelling of human activity and organisa tion on the one hand and to provide the theoretical basis for the computer program constructs on the other."
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 uncertainty and nu merical approaches are often distinguished. Although this distinction is somewhat misleading, it is used as a means to structure the present volume. This is even to some degree reflected in the two first chapters, which treat fundamental, general methods of computation in systems designed to represent uncertainty. It has been noted early by Shenoy and Shafer, that computations in different domains have an underlying common structure. Essentially pieces of knowledge or information are to be combined together and then focused on some particular question or domain. This can be captured in an algebraic structure called valuation algebra which is described in the first chapter. Here the basic operations of combination and focus ing (marginalization) of knowledge and information is modeled abstractly subject to simple axioms."
Goal Directed Proof Theory presents a uniform and coherent methodology for automated deduction in non-classical logics, the relevance of which to computer science is now widely acknowledged. The methodology is based on goal-directed provability. It is a generalization of the logic programming style of deduction, and it is particularly favourable for proof search. The methodology is applied for the first time in a uniform way to a wide range of non-classical systems, covering intuitionistic, intermediate, modal and substructural logics. The book can also be used as an introduction to these logical systems form a procedural perspective. Readership: Computer scientists, mathematicians and philosophers, and anyone interested in the automation of reasoning based on non-classical logics. The book is suitable for self study, its only prerequisite being some elementary knowledge of logic and proof theory.
suchquestionsforcenturies(unrestrictedbythecapabilitiesofanyhard- ware). Theprinciplesgoverningtheinteractionofseveralprocesses,forexample, areabstractansimilartoprinciplesgoverningthecooperationoftwolarge organisation.Adetailedrulebasedeffectivebutrigidbureaucracyisvery muchsimilartoacomplexcomputerprogramhandlingandmanipulating data. Myguessisthattheprinciplesunderlyingoneareverymuchthe sameasthoseunderlyingtheother. Ibelievethedayisnotfarawayinthefuturewhenthecomputerscientist willwakeuponemorningwiththerealisationthatheisactuallyakindof formalphilosopher! TheprojectednumberofvolumesforthisHandbookisabout18.The subjecthasevolvedanditsareashavebecomeinterrelatedtosuchanextent thatitnolongermakessensetodedicatevolumestotopics.However,the volumesdofollowsomenaturalgroupingsofchapters. Iwouldliketothankourauthorsarereadersfortheircontributionsand theircommitmentinmakingthisHandbookasuccess. Thanksalsoto ourpublicationadministratorMrsJ.Spurrforherusualdedicationand excellenceandtoKluwerAcademicPublishersfortheircontinuingsupport fortheHandbook. DovGabbay King'sCollegeLondon x Logic II IT Natural Program Artificialin- Logic p- language controlspec- telligence gramming processing ification, verification, concurrency Temporal Expressive Expressive Planning. Extension of logic poweroftense power for re- Time depen- Horn clause operators. currentevents. dent data. with time Temporal Specification Eventcalculus. capability. indices. Sepa- of tempo- Persistence Eventcalculus. rationofpast ral control. throughtime- Temporallogic fromfuture Decisionprob- the Frame programming. Problem.Tem- lems. Model checking. poral query language. temporal transactions. Modal logic. generalised Actionlogic Beliefrevision. Negation by Multi-modal quantifiers Inferential failure and logics databases modality Algorithmic Discourse rep- New logics. Generaltheory Proceduralap- proof resentation. Generic theo- of reasoning. proachtologic Direct com- remprovers Non-monotonic putation on systems linguisticinput Non- Resolving Loopchecking. Intrinsiclogical Negation by monotonic ambigui- Non-monotonic discipline for failure.Deduc- reasoning ties. Machine decisionsabout AI. Evolving tivedatabases translation. loops. Faults and com- Document insystems. municating classification. databases Relevance theory Probabilistic logicalanalysis Realtimesys- Expert sys- Semantics for and fuzzy oflanguage tems tems.Machine logicprograms logic learning Intuitionistic Quantifiers in Constructive Intuitionistic Horn clause logic logic reasoning and logicisabetter logic is really proof theory logical basis intuitionistic.
The notion of negation is one of the central logical notions. It has been studied since antiquity and has been subjected to thorough investigations in the development of philosophical logic, linguistics, artificial intelligence and logic programming. The properties of negation-in combination with those of other logical operations and structural features of the deducibility relation-serve as gateways among logical systems. Therefore negation plays an important role in selecting logical systems for particular applications. At the moment negation is a 'hot topic', and there is an urgent need for a comprehensive account of this logical key concept. We therefore have asked leading scholars in various branches of logic to contribute to a volume on "What is Negation?." The result is the present neatly focused collection of re search papers bringing together different approaches toward a general characteri zation of kinds of negation and classifications thereof. The volume is structured into four interrelated thematic parts. Part I is centered around the themes of Models, Relevance and Impossibility. In Chapter 1 (Negation: Two Points of View), Arnon Avron develops two characteri zations of negation, one semantic the other proof-theoretic. Interestingly and maybe provokingly, under neither of these accounts intuitionistic negation emerges as a genuine negation. J. Michael Dunn in Chapter 2 (A Comparative Study of Various Model-theoretic Treatments of Negation: A History of Formal Negation) surveys a detailed correspondence-theoretic classifcation of various notions of negation in terms of properties of a binary relation interpreted as incompatibility."
This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as logic itself.
It is with great pleasure that we are presenting to the community the second edition of this extraordinary handbook. It has been over 15 years since the publication of the first edition and there have been great changes in the landscape of philosophical logic since then. The first edition has proved invaluable to generations of students and researchers in formal philosophy and language, as well as to consumers of logic in many applied areas. The main logic artiele in the Encyelopaedia Britannica 1999 has described the first edition as 'the best starting point for exploring any of the topics in logic'. We are confident that the second edition will prove to be just as good. ! The first edition was the second handbook published for the logic commu nity. It followed the North Holland one volume Handbook 0/ Mathematical Logic, published in 1977, edited by the late Jon Barwise. The four volume Handbook 0/ Philosophical Logic, published 1983-1989 came at a fortunate temporal junction at the evolution of logic. This was the time when logic was gaining ground in computer science and artificial intelligence cireles. These areas were under increasing commercial press ure to provide devices which help and/or replace the human in his daily activity. This pressure required the use of logic in the modelling of human activity and organisa tion on the one hand and to provide the theoretical basis for the computer program constructs on the other.
Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities. The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.
Belief change is an emerging field of artificial intelligence and information science dedicated to the dynamics of information and the present book provides a state-of-the-art picture of its formal foundations. It deals with the addition, deletion and combination of pieces of information and, more generally, with the revision, updating and fusion of knowledge bases. The book offers an extensive coverage of, and seeks to reconcile, two traditions in the kinematics of belief that often ignore each other - the symbolic and the numerical (often probabilistic) approaches. Moreover, the work encompasses both revision and fusion problems, even though these two are also commonly investigated by different communities. Finally, the book presents the numerical view of belief change, beyond the probabilistic framework, covering such approaches as possibility theory, belief functions and convex gambles. The work thus presents a unified view of belief change operators, drawing from a widely scattered literature embracing philosophical logic, artificial intelligence, uncertainty modelling and database systems. The material is a clearly organised guide to the literature on the dynamics of epistemic states, knowledge bases and uncertain information, suitable for scholars and graduate students familiar with applied logic, knowledge representation and uncertain reasoning. |
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