Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
The traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of c...
Yll Haxhimusa, Walter G. Kropatsch, Zygmunt Pizlo,...
In this paper, we present a scalable fully distributed version of a Mobile Backbone Network Topology Synthesis Algorithm (MBN-TSA) for constructing and maintaining a dynamic backb...
Humanoid robot is expected as a rational form of machine to act in the real human environment and support people through interaction with them. Current humanoid robots, however, l...
—In this paper, we extend the load sharing framework to study how to effectively perform flow-based traffic splitting in multipath communication networks. The generalized load sh...