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Gradient-based Self-organisation Patterns of Anticipative Adaptation

Danilo Pianini, Mirko Viroli, Sara Montagna
The self-organisation Gradient pattern is known to be a key spatial data structure to make information local to its source become global knowledge, and to dynamically and adaptively steer agents to that source even in mobile and faulty environments – e.g. when obstacles unpredictably appear. In this paper we conceive new self-organisation mechanisms built upon this pattern to tackle anticipative adaptation. We ensure that the retrieval of a target of interest proactively reacts to locally-available information about future events, namely, the knowledge about future obstacles (e.g., expected jams or road interruption in a traffic control scenario) is used to emergently compute alternative and faster paths.
Presented by Danilo Pianini
6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012)
Lyon, France, 11/09/2012