… a broad perspective on uncertainty and approaches to managing uncertainty. Rather than …
in representing uncertain knowledge. We identify the central role of managing uncertainty to AI …

… ), however, few treatments consider the real-world psychology in the mind of the economic
agent in the face of an ontologically uncertain world, instead focusing largely on the emergent …

Advanced visual surveillance systems not only need to track moving objects but also interpret
their patterns of behaviour. This means that solving the information integration problem …

… efficiently with a model of a dynamic and uncertain world. The model will have both symbolic
and … of the world's uncertainty. Our job will be to integrate the two sorts of information. …

… But this conflates with usage in practice where there is uncertainty about what things are in
this world. In vision and language understanding, for example, the system would discover the …

… , artificial intelligence was bound to deal with various frameworks for the handling of uncertainty:
… of two basic frameworks for representing uncertainty: probability theory and possibility …

In this paper we show that it can be beneficial to have a high-level vision component that
guides the reasoning of the whole vision system when interpreting a dynamic and uncertain …

… Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of
sustainable practices in an uncertain … decisionmaking in an uncertain environment. SCOPUS …

A long-standing goal of AI is to enable robots to plan in the face of uncertain and incomplete
information, and to handle task failure intelligently. This paper shows how to achieve this. …

… with this all-important knowledge about uncertainty? This dissertation proposes an artificial
intelligence approach-a model of heuristic reasoning about uncertainty implemented as a …