Richmond H. Thomason

Bio: Richmond H. Thomason is an academic researcher from University of Michigan. The author has contributed to research in topics: Inheritance (object-oriented programming) & Non-monotonic logic. The author has an hindex of 32, co-authored 116 publications receiving 4432 citations. Previous affiliations of Richmond H. Thomason include University of Maryland, College Park & Carnegie Mellon University.

A clash of intuitions: the current state of nonmonotonic multiple inheritance systems

Abstract: Early attempts at combining multiple inheritance with nonmonotonic reasoning were based on straight forward extensions of tree-structured inheritance systems, and were theoretically unsound. In The Mathematics of Inheritance Systems, or TMOIS, Touretzky described two problems these systems cannot handle: reasoning in the presence of true but redundant assertions, and coping with ambiguity. TMOIS provided a definition and analysis of a theoretically sound multiple inheritance system, accompanied by inference algorithms. Other definitions for inheritance have since been proposed that are equally sound and intuitive, but do not always agree with TMOIS. At the heart of the controversy is a clash of intuitions about certain fundamental issues such as skepticism versus credulity, the direction in which inheritance paths are extended, and classical versus intuitive notions of consistency. Just as there are alternative logics, there may be no single "best" approach to nonmonotonic multiple inheritance.

Combinations of Tense and Modality

Abstract: Physics should have helped us to realise that a temporal theory of a phenomenon X is, in general, more than a simple combination of two components: the statics of X and the ordered set of temporal instants. The case in which all functions from times to world-states are allowed is uninteresting; there are too many such functions, and the theory has not begun until we have begun to restrict them. And often the principles that emerge from the interaction of time with the phenomena seem new and surprising. The most dramatic example of this, perhaps, is the interaction of space with time in relativistic space-time.

A skeptical theory of inheritance in nonmonotonic semantic networks

Abstract: This paper describes a new approach to inheritance reasoning in semantic networks allowing for multiple inheritance with exceptions The approach leads to a definition of inheritance that is both theoretically sound and intuitively attractive: it yields unambiguous results applied to any acyclic semantic net, and these results conform to our own intuitions in the cases in which the intuitions themselves are firm and unambiguous Since, however, the definition provided here is based on an alternative, skeptical view of inheritance reasoning, it does not always agree with previous definitions when it is applied to nets about which our intuitions are unsettled, or in which different reasoning strategies could naturally be expected to yield distinct results

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

Abstract: From the Publisher: Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty—and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition—in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Intelligent Agents: Theory and Practice

Abstract: The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents;researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

Phonology and Syntax: The Relation between Sound and Structure

Abstract: A fundamentally new approach to the theory of phonology and its relation to syntax is developed in this book, which is the first to address the question of the relation between syntax and phonology in a systematic way.This general theory differs from its predecessors in the generative tradition in several respects. By arguing that the intonational structure of a sentence determines certain aspects of its stress pattern or rhythmic structure, and not vice versa, it provides a novel view of the intonation-stress relation. It also offers a new theory of the focus-prosody relation that solves a variety of classic puzzles and involves an appeal to the place of a focused constituent in the predicate-argument structure of the sentence. The book also includes other novel features, among them a development of the metrical grid theory of stress (including a complete treatment of English word stress in this framework), the representation of juncture in terms of "silent" positions in the metrical grid (with a treatment of sandhi in terms of this rhythmic juncture), and a "rhythmic" nonsyntactic approach to the basic phonology of function words in EnglishElisabeth 0. Selkirk is Professor of Linguistics at the University of Massachusetts, Amherst. This book is tenth in the series, Current Studies in Linguistics.