Abstract
The parameter setting of an algorithm that will result in optimal performance is a tedious task for users who spend a lot of time fine-tuning algorithms for their specific problem domains. This paper presents a multi-agent tuning system as a framework to set the parameters of a given algorithm which solves a specific problem. Besides, such a configuration is generated taking into account the current problem instance to be solved. We empirically evaluate our multi-agent tuning system using the configuration of a genetic algorithm applied to the root identification problem. The experimental results show the validity of the proposed model.
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Pavón, R., Glez-Peña, D., Laza, R., Díaz, F., Luzón, M.V. (2009). A Multi-Agent System Approach for Algorithm Parameter Tuning. In: Demazeau, Y., Pavón, J., Corchado, J.M., Bajo, J. (eds) 7th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2009). Advances in Intelligent and Soft Computing, vol 55. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00487-2_15
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DOI: https://doi.org/10.1007/978-3-642-00487-2_15
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