: Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms d...
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
Abstract— This paper presents coverage algorithms for mobile sensor networks in which agents have limited power to move. Rather than making use of a constrained optimization tech...
We present exact characterizations of structures on which the greedy algorithm produces optimal solutions. Our characterization, which we call matroid embeddings, complete the par...
Paul Helman, Bernard M. E. Moret, Henry D. Shapiro
Abstract—Interest in multimodal optimization function is expanding rapidly since real-world optimization problems often require the location of multiple optima in the search spac...