In this paper, we consider a hybrid solution to the sensor network position inference problem, which combines a real-time filtering system with information from a more expensive,...
Dimitri Marinakis, David Meger, Ioannis M. Rekleit...
Abstract. This paper studies the inducement of sequentiality in genetic algorithms (GAs) for uniformly-scaled problems. Sequentiality is a phenomenon in which sub-solutions converg...
Kei Ohnishi, Kumara Sastry, Ying-Ping Chen, David ...
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
It is known that the dynamics of best response in an environment of non-cooperative users may converge to a good solution when users play sequentially, but may cycle far away from...
We describe HDL, an algorithm that learns HTN domain descriptions by examining plan traces produced by an expert problem-solver. Prior work on learning HTN methods requires that a...