What is it about?
Central to this approach is the implementation of a collective adaptation engine (CAE) able to solve issues in a collective fashion. The approach is instantiated in the context of a smart mobility scenario through which its main features are illustrated. To demonstrate the approach in action and evaluate it, we exploit the DeMOCAS framework, simulating the operation of an urban mobility scenario. We have executed a set of experiments with the goal to show how the CAE performs in terms of feasibility and scalability. With this approach, we are able to demonstrate how collective adaptation opens up new possibilities for tackling urban mobility challenges making it more sustainable respect to selfish and competitive behaviours.
Photo by Mika Baumeister on Unsplash
Why is it important?
How collective adaptation opens up new possibilities for tackling urban mobility challenges making it more sustainable respect to selfish and competitive behaviours.
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This page is a summary of: Collective Adaptation through Multi-Agents Ensembles, ACM Transactions on Autonomous and Adaptive Systems, June 2019, ACM (Association for Computing Machinery), DOI: 10.1145/3355562.
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