Instructions: In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
Input: Traditionally, most of the proposed probabilistic models of decision under uncertainty rely on numerical measures and representations. Alternative proposals call for qualitative (non-numerical) treatment of uncertainty, based on preference relations and belief orders. The automation of both numerical and non-numerical frameworks surely represents a preliminary step in the development of inference engines of intelligent agents, expert systems, and decision-support tools. In this paper we exploit Answer Set Programming to formalize and reason about uncertainty expressed as belief orders. The availability of ASP-solvers supports the design of automated tools to handle such formalizations. Our proposal reveals particularly suitable whenever the domain of discernment is partial. We first illustrate how to automatically "classify ^^, according to the most well-known uncertainty frameworks, any given qualitative uncertainty assessment. Then, we show how to compute an enlargement of the assessment, to any other new inference target.
Output:
Management of uncertainty orderings through ASP