Artificial intelligence publications
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Directing Agent Communities: An Initial Framework
This paper presents a framework for directability of a community of agents by a human supervisor that focuses on three dimensions: adjustable agent autonomy, strategy preference, and community-level constraints.
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The genome of the natural genetic engineer Agrobacterium tumefaciens C58
The 5.67-megabase genome of the plant pathogen Agrobacterium tumefaciens C58 consists of a circular chromosome, a linear chromosome, and two plasmids.
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The .geo-web: A Scalable Index for the Digital Earth
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Structured Argumentation for Analysis
We are developing a new methodology that retains the ease-of-use, familiarity, and (some of) the free-form nature of informal methods, while benefiting from the rigor, structure, and potential for automation…
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Reusing Prior Knowledge: Problems and Solutions
In this paper, we focus on the process of reuse and report a case study on constructing a KB by reusing existing knowledge. The reuse process involved the following steps:…
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Measuring the Self-Consistency of Stereo Algorithms
A new approach to characterizing the performance of point-correspondence algorithms is presented. Instead of relying on any "ground truth", it uses the self-consistency of the outputs of an algorithm independently…
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Multiple-Target Tracking and Data Fusion via Probabilistic Mapping
A new approach is taken to address the various aspects of the multi-sensor, multi-target tracking (MTT) problem in dense and noisy environments. Instead of fixing the trackers on the potential…
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A Guide to SNARK
Snark, SRI's New Automated Reasoning Kit, is a theorem prover intended for applications in artificial intelligence and software engineering. This document is an example-driven tutorial introduction to snark that will…
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Multiple-Target Tracking in Dense, Noisy Environments: A Probabilistic Mapping Perspective
A new approach is taken to address the various aspects of the multiple-target tracking (MTT) problem in dense and noisy environments.
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MAESTRO: Conductor of Multimedia Analysis Technologies
MAESTRO is a research and demonstration system developed at SRI International for exploring the contribution of a variety of analysis technologies
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XOL: An XML-Based Ontology Exchange Language
This document describes a language called XOL, is designed to provide a format for exchanging ontology definitions among a set of interested parties.
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Maximum Entropy Markov Models for Information Extraction and Segmentation
We address: modeling sequential data with HMMs, problems with previous methods: motivation, the maximum entropy Markov model, segmentation of FAQs: experiments and results.