Over the past five years the Artificial Intelligence Center at SRI has been developing a new technology to address the problem of automated information management within real-world contexts.
Any intelligent system that operates in a moderately complex or unpredictable environment must be reactive — that is, it must respond dynamically to changes in its environment.
Current shape-from-shading and shape-from-texture methods are applicable only to smooth surfaces, while real surfaces are often rough and crumpled. To extend such methods to real surfaces we must have a model that also applies to rough surfaces.
The syntactic structure of a sentence often manifests quite clearly the predicate-argument structure and relations of grammatical subordination. But scope dependencies are not so transparent.
This paper describes a morphological analyzer which, when parsing a word, uses two sets of rules: describing the syntax of words, and rules describing facts about orthography.
A new approach to the formulation and solution of the problem of recovering scene topography from a stereo image pair is presented. The approach circumvents the need to solve the correspondence problem, returning a solution that makes surface interpolation unnecessary.
Existing models of plan inference (PI) in conversation have assumed that the agent whose plan is being inferred (the actor) and the agent drawing the inference (the observer) have identical beliefs about actions in the domain.
