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David Israel

Bio: David Israel is an academic researcher from SRI International. The author has contributed to research in topics: Knowledge representation and reasoning & Natural language. The author has an hindex of 30, co-authored 64 publications receiving 5549 citations. Previous affiliations of David Israel include Artificial Intelligence Center & Stanford University.


Papers
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Journal ArticleDOI
01 Sep 1988
TL;DR: A high‐level specification of the practical‐reasoning component of an architecture for a resource‐bounded rational agent, where a major role of the agent's plans is to constrain the amount of further practical reasoning she must perform.
Abstract: An architecture for a rational agent must allow for means-end reasoning, for the weighing of competing alternatives, and for interactions betwen these two forms of reasoning. Such an architecture must also address the problem of resource boundedness. We sketch a solution of the first problem that points the way to a solution of the second. In particular, we present a high-level specification of the practical-reasoning component of an architecture for a resource-bounded rational agent. In this architecture, a major role of the agent's plans is to constrain the amount of further practical reasoning she must perform.

1,229 citations

Patent
15 Sep 2000
TL;DR: A natural language information querying system includes an indexing facility configured to automatically generate indices of updated textual sources based on one or more predefined grammars and a database coupled to the indexing facilities to store the indices for subsequent searching as discussed by the authors.
Abstract: A natural language information querying system includes an indexing facility configured to automatically generate indices of updated textual sources based on one or more predefined grammars and a database coupled to the indexing facility to store the indices for subsequent searching.

586 citations

Proceedings Article
01 Jan 1993
TL;DR: FASTUS has been evaluated on several blind tests that demonstrate that state-of-the-art performance on information-extraction tasks is obtainable with surprisingly little computational effort.
Abstract: Approaches to text processing that rely on parsing the text with a context-free grammar tend to be slow and error-prone because of the massive ambiguity of long sentences. In contrast, FASTUS employs a nondeterministic finite-state language model that produces a phrasal decomposition of a sentence into noun groups, verb groups and particles. Another finite-state machine recognizes domain-specific phrases based on combinations of the heads of the constituents found in the first pass. FASTUS has been evaluated on several blind tests that demonstrate that state-of-the-art performance on information-extraction tasks is obtainable with surprisingly little computational effort.

469 citations

Posted Content
TL;DR: This decomposition of language processing enables the system to do exactly the right amount of domain-independent syntax, so that domain-dependent semantic and pragmatic processing can be applied to the right larger-scale structures.
Abstract: FASTUS is a system for extracting information from natural language text for entry into a database and for other applications. It works essentially as a cascaded, nondeterministic finite-state automaton. There are five stages in the operation of FASTUS. In Stage 1, names and other fixed form expressions are recognized. In Stage 2, basic noun groups, verb groups, and prepositions and some other particles are recognized. In Stage 3, certain complex noun groups and verb groups are constructed. Patterns for events of interest are identified in Stage 4 and corresponding ``event structures'' are built. In Stage 5, distinct event structures that describe the same event are identified and merged, and these are used in generating database entries. This decomposition of language processing enables the system to do exactly the right amount of domain-independent syntax, so that domain-dependent semantic and pragmatic processing can be applied to the right larger-scale structures. FASTUS is very efficient and effective, and has been used successfully in a number of applications.

334 citations

Proceedings ArticleDOI
06 Nov 1995
TL;DR: SRI International participated in the MUC-6 evaluation using the latest version of SRI's FASTUS system as mentioned in this paper, which is a cascaded finite state transducers, each providing an additional level of analysis of the input and merging of the final results.
Abstract: SRI International participated in the MUC-6 evaluation using the latest version of SRI's FASTUS system [1]. The FASTUS system was originally developed for participation in the MUC-4 evaluation [3] in 1992, and the performance of FASTUS in MUC-4 helped demonstrate the viability of finite state technologies in constrained natural-language understanding tasks. The system has undergone significant revision since MUC-4, and it is safe to say that the current system does not share a single line of code with the original. The fundamental ideas behind FASTUS, however, are retained in the current system: an architecture consisting of cascaded finite state transducers, each providing an additional level of analysis of the input, together with merging of the final results.

241 citations


Cited by
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Journal ArticleDOI
TL;DR: 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 as discussed by the authors ; agent architectures can be thought of as software engineering models of agents; and agent languages are software systems for programming and experimenting with agents.
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.

6,714 citations

Book
01 Dec 1996
TL;DR: Clark as mentioned in this paper argues that the mental has been treated as a realm that is distinct from the body and the world, and argues that a key to understanding brains is to see them as controllers of embodied activity.
Abstract: From the Publisher: The old opposition of matter versus mind stubbornly persists in the way we study mind and brain. In treating cognition as problem solving, Andy Clark suggests, we may often abstract too far from the very body and world in which our brains evolved to guide us. Whereas the mental has been treated as a realm that is distinct from the body and the world, Clark forcefully attests that a key to understanding brains is to see them as controllers of embodied activity. From this paradigm shift he advances the construction of a cognitive science of the embodied mind.

3,745 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap, including performance errors, computational limitations, the wrong norm being applied by the experi- menter, and a different construal of the task by the subject.
Abstract: Much research in the last two decades has demon- strated that human responses deviate from the performance deemed normative according to various models of decision mak- ing and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be inter- preted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experi- menter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance er- rors are a minor factor in the gap; computational limitations un- derlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Un- expected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.

3,068 citations

01 Jan 1995
TL;DR: This paper explores a particular type of rational agent, a BeliefDesire-Intention (BDI) agent, and integrates the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective.
Abstract: The study of computational agents capable of rational behaviour has received a great deal of attention in recent years. Theoretical formalizations of such agents and their implementations have proceeded in parallel with little or no connection between them. Tkis paper explores a particular type of rational agent, a BeliefDesire-Intention (BDI) agent. The primary aim of this paper is to integrate (a) the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective; (b) the implementations of BDI agents from an ideal theoretical perspective and a more practical perspective; and (c) the building of large-scale applications based on BDI agents. In particular, an air-trafflc management application will be described from both a theoretical and an implementation perspective.

3,050 citations

01 May 1986
TL;DR: A new theory of discourse structure that stresses the role of purpose and processing in discourse is explored and various properties of discourse are described, and explanations for the behavior of cue phrases, referring expressions, and interruptions are explored.
Abstract: In this paper we explore a new theory of discourse structure that stresses the role of purpose and processing in discourse. In this theory, discourse structure is composed of three separate but interrelated components: the structure of the sequence of utterances (called the linguistic structure), a structure of purposes (called the intentional structure), and the state of focus of attention (called the attentional state). The linguistic structure consists of segments of the discourse into which the utterances naturally aggregate. The intentional structure captures the discourse-relevant purposes, expressed in each of the linguistic segments as well as relationships among them. The attentional state is an abstraction of the focus of attention of the participants as the discourse unfolds. The attentional state, being dynamic, records the objects, properties, and relations that are salient at each point of the discourse. The distinction among these components is essential to provide an adequate explanation of such discourse phenomena as cue phrases, referring expressions, and interruptions.The theory of attention, intention, and aggregation of utterances is illustrated in the paper with a number of example discourses. Various properties of discourse are described, and explanations for the behavior of cue phrases, referring expressions, and interruptions are explored.This theory provides a framework for describing the processing of utterances in a discourse. Discourse processing requires recognizing how the utterances of the discourse aggregate into segments, recognizing the intentions expressed in the discourse and the relationships among intentions, and tracking the discourse through the operation of the mechanisms associated with attentional state. This processing description specifies in these recognition tasks the role of information from the discourse and from the participants' knowledge of the domain.

2,748 citations