Evolutionary design and behavior analysis of neuromodulatory neural networks for mobile robots control

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Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, background): “At the same time, Kondo (2007) proposed an evolutionary design and behavior analysis of neuromodulatory neural networks for mobile robot control, validating the potential of the method.”
Evolutionary and Computational Advantages of Neuromodulated Plasticity (2008, background): “In (Kondo, 2007), an evolutionary design and behaviour analysis of feed-forward networks with neuromodulators was proposed to fill the gap between simulation and real robotic control.”
Spectrum-Diverse Neuroevolution With Unified Neural Models (2017, background): “The results obtained from using such mechanisms are much more encouraging [35]–[39].”
Artificial Evolution of Plastic Neural Networks: A Few Key Concepts (2014, methodology): “Modulated Hebbian plasticity has been used several times when evolving plastic neural networks [14], [15], [17], [21], [26].”
Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward-based Scenarios (2008, methodology): “Improved performance and adaptation by means of neuromodulation were shown on a real robot in (Kondo, 2007).”
Adaptation of Robot Behaviour through Online Evolution and Neuromodulated Learning (2012, result): “This result is similar to those presented, for instance, in [12, 23].”