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 ...
In this paper we present a probabilistic framework for the reduction in the uncertainty of a moving robot pose during exploration by using a second robot to assist. A Monte Carlo ...
Ioannis M. Rekleitis, Gregory Dudek, Evangelos E. ...
Abstract— This paper explores the problem of efficiently ordering interprocessor communication operations in both statically and dynamically-scheduled multiprocessors for iterat...
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
—MapReduce has become increasingly popular as a powerful parallel data processing model. To deploy MapReduce as a data processing service over open systems such as service orient...