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Pharaon ants inspire an AI algorithm with applications such as drug search or logistic optimization
Pharaon ants inspire an AI algorithm with applications such as drug search or logistic optimization

22/DEC/2020
22/DEC/2020

 

IIIA-CSIC scientists improve an algorithm inspired by the behaviour of Pharaon ants. These ants use pheromones for setting ‘no-entry’ signals, which is an example of learning based on negative feedback. It enables to improve optimization techniques for many sectors, both in industry and in scientific research. In the research, Christian Blum (Artificial Intelligence Research Institutte) and the doctoral student Teddy Nurcahyadi have designed the first general mechanism to incorporate negative learning in a way that clearly benefits and improves the ACO technique.

The whole article can be read at: https://rdcsic.dicat.csic.es/en/tecnologias-fisicas-2/117-projects/581-pharaon-ants-inspire-an-artificial-intelligence-algorithm-with-applications-such-as-drug-search-or-logistic-optimization

IIIA-CSIC scientists improve an algorithm inspired by the behaviour of Pharaon ants. These ants use pheromones for setting ‘no-entry’ signals, which is an example of learning based on negative feedback. It enables to improve optimization techniques for many sectors, both in industry and in scientific research. In the research, Christian Blum (Artificial Intelligence Research Institutte) and the doctoral student Teddy Nurcahyadi have designed the first general mechanism to incorporate negative learning in a way that clearly benefits and improves the ACO technique.

The whole article can be read at: https://rdcsic.dicat.csic.es/en/tecnologias-fisicas-2/117-projects/581-pharaon-ants-inspire-an-artificial-intelligence-algorithm-with-applications-such-as-drug-search-or-logistic-optimization

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