SRI International is implementing a complete, state-of the-art stereo system that will produce dense three-dimensional (3D) data from stereo pairs of intensity images.
In searching for universal constraints on the class of natural languages, linquists have investigated a number of formal properties, including that of context-freeness.
It has been argued that knowledge-based systems (KBS) must reason from evidential information–i.e., information that is to some degree uncertain, imprecise, and occasionally inaccurate.
In order to plan operations where knowledge of significant elements is imprecise and uncertain, a means of characterizing the situation in terms of the various factors that may influence those operations must be provided.
Reasoning from uncertain, incomplete, and sometimes inaccurate information is necessary whenever any system is to interact in an intelligent way with its environment.
R. Schrag, M. Pool, Vinay K. Chaudhri, R.C. Kahlert, J. Powers, Philip R. Cohen, J. Fitzgerald, & S. Mishra
We describe a large-scale experiment in which non-artificial intelligence subject matter experts - with neither artificial intelligence background nor extensive training in the task - author knowledge bases following a challenge problem specification with a strong question-answering component.
In this paper I argue that an intentional methodology is appropriate in the design of robot agents in cooperative planning domains–at least in those domains that are sufficiently open-ended to require extensive reasoning about the environment (including other agents).
