This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Data products generated from remotely-sensed, geospatial imagery (RSI) used in emerging areas, such as global climatology, environmental monitoring, land use, and disaster managem...
We develop a novel framework for supporting e-Science applications that require streaming of information between sites. Using a Synchronous Dataflow (SDF) model, our framework inco...
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...
On-line decision making often involves query processing over time-varying data which arrives in the form of data streams from distributed locations. In such environments typically...