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Human vs. Deep Neural Network Performance at a Leader Identification Task
Human AI Robot Teaming (HART)
LocationGrand Salon VII
DescriptionControl of robotic swarms through control over a leader(s) has become the dominant approach. Resilience to attrition is one of the primary advantages attributed to swarms yet the presence of leader(s) makes them vulnerable to decapitation. Algorithms which allow a swarm to hide its leader are one solution. We replace conventional controllers with neural networks to make them more amenable to training. Swarms and an adversary were trained and tested in 4 phases: 1- follow leader, 2-adversary to recognize leader, 3-swarm to hide leader, and 4-swarm and adversary compete to hide and recognize the leader. While the NN adversary was more successful in identifying leaders without deception, humans did better in conditions in which the swarm was trained to hide its leader from the NN adversary. The study illustrates difficulties likely to emerge in arms races between machine learners and the potential role humans may play in moderating them.