Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
A high assurance system requires both functional and nonfunctional correctness before the system is put into operation. To examine whether a system’s actual performance complies...
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 this paper we investigate the relationship between two problems, related to distributed systems, that are of particular interest in the context of Service Oriented Computing: at...
A notorious open problem in the field of rendezvous search is to decide the rendezvous value of the symmetric rendezvous search problem on the line, when the initial distance apar...
Qiaoming Han, Donglei Du, Juan Vera, Luis F. Zulua...