Artificial intelligence publications

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…

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…

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…

A new approach is taken to address the various aspects of the multiple-target tracking (MTT) problem in dense and noisy environments.

MAESTRO is a research and demonstration system developed at SRI International for exploring the contribution of a variety of analysis technologies

We address: modeling sequential data with HMMs, problems with previous methods: motivation, the maximum entropy Markov model, segmentation of FAQs: experiments and results.

In this paper, we argue that improved usability requires a new representational layer that captures metatheoretic properties of a planning domain.

The goal of this project was to enable knowledge engineers to construct knowledge bases (KBs) faster. To achieve this goal, we investigated two techniques: knowledge reuse and axiom templates. The…

This paper investigates whether a machine can automatically learn the task of finding, within a large collection of candidate responses, the answers to questions.

This paper introduces two contrasting methods for planning with conflicting advice, suited to different user requirements. Soft enforcement embodies a heuristic approach that prefers planning choices that are consistent with…