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This work proposes a biologically inspired system for the coordination of multiple and possible conflicting behaviours in an autonomous mobile robot, devoted to explore novel scenarios while ensuring its internal variables dynamics. The proposed evolutionary artificial homeostatic system, derived from the study of how an organism would self-regulate in order to keep its essential variables within a limited range (homeostasis), is composed of an artificial endocrine system, including two hormones and two hormone receptors, and also three previously evolved NSGasNet artificial neural networks. It is shown that the integration of receptors enhance the system robustness without incorporating to the three evolved NSGasNets more a priori knowledge. The experiments conducted also show that the proposed multi-hormone evolutionary artificial homeostatic system is able to successfully coordinate a multiple and conflicting behaviours task, being also robust enough to cope with internal and external disruptions.