Predicting stock market movements is always difficult. Investors try to guess a stock's behavior, but it often backfires. Thumb rules and intuition seems to be the major indi...
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
We develop a formal framework for comparing different versions of ontologies, and apply it to ontologies formulated in terms of DL-Lite, a family of `lightweight' description...
Roman Kontchakov, Frank Wolter, Michael Zakharyasc...