This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
In Multi-agent based simulation (MABS) systems, computational models are built as multi-agent systems (MAS). Replication of these models can contribute to improve the reliability o...
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
In this paper we propose a novel finite-horizon, discrete-time, time-varying filtering method based on the robust semidefinite programming (SDP) technique. The proposed method prov...
Lingjie Li, Zhi-Quan Luo, Timothy N. Davidson, Kon...
Online Convex Programming (OCP) is a recently developed model of sequential decision-making in the presence of time-varying uncertainty. In this framework, a decisionmaker selects ...