The social brain hypothesis posits that the evolution of big brains (neural complexity) in groups of social organisms is the evolutionary result of cognitive challenges associated with various complex interactions and the need to process and solve complex social tasks. This study aims to investigate the environmental and evolutionary conditions under which neural complexity evolves without sacrificing collective behavioral efficacy. Using an evolutionary collective robotics system this research evaluates the impact of imposing a fitness cost on evolving increased neural complexity in robot groups that must operate (accomplish cooperative tasks) in environments of varying complexity. Results indicate that for all environments tested, imposing a cost on neural complexity induces the evolution of smaller neural controllers that are comparably effective to more complex controllers.
CITATION STYLE
Nagar, D., Furman, A., & Nitschke, G. (2020). The cost of big brains in groups. In Proceedings of the 2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019 (pp. 404–411). MIT Press. https://doi.org/10.1162/isal_a_00193.xml
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