Exploiting abstractions for grammar-based learning of complex multi-agent behaviours

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Samarasinghe:2021:IJIS,

• author = "Dilini Samarasinghe and Michael Barlow and Erandi Lakshika and Kathryn Kasmarik",
• title = "Exploiting abstractions for grammar-based learning of complex multi-agent behaviours",
• journal = "International Journal of Intelligent Systems",
• year = "2021",
• volume = "36",
• number = "11",
• pages = "6273--6311",
• month = nov,
• keywords = "genetic algorithms, genetic programming, grammatical evolution, abstractions, curriculum learning, incremental learning, multi-agent systems, parallel learning",
• DOI = "doi:10.1002/int.22550",
• abstract = "We present a grammar-based evolutionary approach that incorporates abstractions to learn complex collective behaviours through their simpler representations. We propose modifications to the grammar syntax design and genome structure to facilitate evolution of abstractions in separate genome partitions. Two abstraction techniques based on behavioural decomposition and environmental scaffolding are presented to derive these simpler representations. Parallel and incremental learning architectures incorporated with grammatical evolution (GE) are investigated with three complex problems to evaluate their potential in generating collective multi-agent behaviours. The results infer that both learning architectures surpass a generic GE model in performance for evolving complex behaviours. Furthermore, using environmental scaffolding reduces the robustness of the model than when only the behavioural decomposition technique is used. However, it has more potential to generate solutions with better fitness than when scaffolding is not used. The evaluations suggest that, by incorporating abstraction learning architectures with grammar-based evolution can significantly improve the performance of an agent system in complex problem domains.",

}

Genetic Programming entries for Dilini Samarasinghe Michael Barlow Erandi Hene Kankanamge Kathryn Kasmarik

Citations