The saturation strategy for symbolic state-space generation is very effective for globally-asynchronous locally-synchronous discrete-state systems. Its inherently sequential natu...
Modern AI planners use different strategies to simplify the complexity of current planning problems and turn them more affordable. In this paper, we present a new approach that div...
In this work, we address the biclustering of gene expression data with evolutionary computation, which has been proven to have excellent performance on complex problems. In express...
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
This paper proposes a novel path planning algorithm of 3-D articulated robots with moving bases based on a generalized potential field model. The approach computes, similar to th...