— In this paper we show that significant simplicity can be exploited for pricing-based control of large networks. We first consider a general loss network with Poisson arrivals...
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
Automated software verification and path-sensitive program analysis require the ability to distinguish executable program paths from those that are infeasible. To achieve this, pro...
Sampling-based nonholonomic and kinodynamic planning iteratively constructs solutions with sampled controls. A constructed trajectory is returned as an acceptable solution if its &...
Agent-based modelling approaches are usually based on logical languages, whereas in many areas dynamical system models based on differential equations are used. This paper shows ho...