David J. Israel

Plans and Resource-Bounded Practical Reasoning

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 agents plans is to constrain the amount of further practical reasoning she must perform.

SRI International FASTUS system: MUC-6 test results and analysis

SRI International participated in the MUC-6 evaluation using the latest version of SRIs 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.

FASTUS: a system for extracting information from text

FASTUS is a (slightly permuted) acronym for Finite State Automaton Text Understanding System. It is a system for extracting information from free text in English (Japanese is under development), for entry into a database, and potentially for other applications. It works essentially as a set of cascaded, nondeterministic finite state automata.

SRI International: description of the FASTUS system used for MUC-4

FASTUS is a (slightly permuted) acronym for Finite State Automaton Text Understanding System. It is a system for extracting information from free text in English, and potentially other languages as well, for entry into a database, and potentially for other applications. It works essentially as a cascaded, nondeterministic finite state automaton.

Reflections on Gödel's and Gandy's Reflections on Turing's Thesis

We sketch the historical and conceptual context of Turings analysis of algorithmic or mechanical computation. We then discuss two responses to that analysis, by Gödel and by Gandy, both of which raise, though in very different ways. The possibility of computation procedures that cannot be reduced to the basic procedures into which Turing decomposed computation. Along the way, we touch on some of Clelands views.

Mixed-initiative visual analytics using task-driven recommendations

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support discovery and sensemaking tasks, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with analytic models, such as inferring data models from user interactions to steer the underlying models of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Sensemaking researchers have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present candidate design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences about user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.

Principles of template design

The functionality of systems that extract information from texts can be specified quite simply: the input is a stream of texts and the output is some representation of the information to be extracted. Hence, the problem of template design is an instance of the problem of knowledge representation. In particular, it is the problem of representing essential facts about situations in a way that can mediate between texts that describe those situations and a variety of applications that involve reasoning about them.The research on which we report here is directed at elucidating principles of template design and at compiling these, with examples, in a manual for template designers.

Some remarks on the place of logic in knowledge representation

What is the place of logic in knowledge representation? It is argued that the answer to this question depends on what one means by logic. Various alternative conceptions are briefly scouted, with an eye to separating out what are. in fact, separate issues.

SRI's Tipster II Project

The principal barrier to the widespread use of information extraction technology is the difficulty in defining the patterns that represent ones information requirements. Much of the work that has been done on SRIs Tipster II project has been directed at overcoming this barrier. In this paper, after some background on the basic structure of the FASTUS system, we present some of these developments. Specifically, we discuss the declarative pattern specification language FastSpec, compile-time transformations, and adapting rules from examples. In addition, we have developed the basic capabilities of FASTUS. We describe our efforts in one are---coreference resolution. We are now experimenting with the use of FASTUS in improving document retrieval and this is also described.

Concepts of Information: Comparative Axiomatics

Jon Barwise has drawn a potentially unflattering analogy between the Bronze Age and the Information Age. People in the Bronze Age were quite expert at working with bronze, but it was a long time after the end of the Bronze Age, that scientists were able to determine the true nature of bronze. Indeed, by the time researchers got around to providing the requisite materials for an adequate theory of the nature of bronze, all the denizens of the Bronze Age were long dead. Mutatis mutandis for us and information? The fond hope is that what follows will go some distance toward allaying fears of history repeating itself in this regard.