This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of...
In this paper we report some progress in applying timed automata technology to large-scale problems. We focus on the problem of finding maximal stabilization time for combinationa...
We focus on neuro-dynamic programming methods to learn state-action value functions and outline some of the inherent problems to be faced, when performing reinforcement learning in...
Learning on real robots in an real, unaltered environment provides an extremely challenging problem. Many of the simplifying assumptions made in other areas of learning cannot be ...
This paper considers the problem of clustering a partially observed unweighted graph – i.e. one where for some node pairs we know there is an edge between them, for some others ...