Belief functions induced by multimodal probability density functions, an application to the search and rescue problem
In this paper, we propose a new method to generate a continuous belief functions from a multimodal probability distribution function defined over a continuous domain. We generalize Smets' approach in the sense that focal elements of the resulting continuous belief function can be disjoint sets of the extended real space of dimension . We then derive the continuous belief function from multimodal probability density functions using the least commitment principle. We illustrate the approach on two...