Computer science and engineering nowadays appears to be challenged (and driven) by technological progress and quantitative growth. Among the technological progress challenges are ...
Learning Bayesian networks from data has been studied extensively in the evolutionary algorithm communities [Larranaga96, Wong99]. We have previously explored extending some of the...
A model-driven reuse approach that is based on an organization’s Enterprise Architecture (EA) and on the Unified Modeling Language (UML) is proposed. The framework embodying th...
Multiagent probabilistic reasoning with multiply sectioned Bayesian networks requires interfacing agent subnets (the modeling task) subject to a set of conditions. To specify the ...
In this paper the hardware and software design of the CMU Hammerhead middle-size robot team are presented. The team consists of 4 fully autonomous robots with wireless communicatio...
Rosemary Emery, Tucker R. Balch, Rande Shern, Kevi...