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 ...
Abstract. We consider the problem of estimating the locations of mobile agents by fusing the measurements of displacements of the agents as well as relative position measurements b...
Although timetabling has long been studied through constraint satisfaction based techniques, along with many alternatives, only recently work has been reported where distributed t...
Multiagent distributed resource allocation requires that agents act on limited, localized information with minimum communication overhead in order to optimize the distribution of ...
a growing need to study abstract problems in distributed multi-agent systems in a systematic way, as well as to provide a qualitative mathematical framework in which to compare po...