We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
Non-traditional environments often change rapidly without forewarning, are difficult or impossible to control, and have other environmental and operational constraints that cannot...
Gisele Bennett, Gitte Lindgaard, Bruce Tsuji, Kay ...
— In this paper we present a heuristic approach to planning in an environment with moving obstacles. Our approach assumes that the robot has no knowledge of the future trajectory...
This study tries to apply wireless technologies to build a highly interactive environment. For this purpose, this study first identifies four types of interaction between the memb...
With the advent of large scale heterogeneous environments, there is a need for matching and scheduling algorithms which can allow multiple DAG-structured applications to share the...