  Coordination and cooperation between humans and autonomous agents in
cooperative games raises interesting questions of human decision making and
behaviour changes. Here we report our findings from a group formation game in a
small-world network of different mixes of human and agent players, aiming to
achieve connected clusters of the same colour by swapping places with
neighbouring players using non-overlapping information. In the experiments the
human players are incentivized by rewarding to prioritize their own cluster
while the model of agents' decision making is derived from our previous
experiment of purely cooperative game between human players. The experiments
were performed by grouping the players in three different setups to investigate
the overall effect of having cooperative autonomous agents within teams. We
observe that the change in the behavior of human subjects adjusts to playing
with autonomous agents by being less risk averse, while keeping the overall
performance efficient by splitting the behaviour into selfish and cooperative
in the two actions performed during the rounds of the game. Moreover, results
from two hybrid human-agent setups suggest that the group composition affects
the evolution of clusters. Our findings indicate that in purely or lesser
cooperative settings, providing more control to humans could help in maximizing
the overall performance of hybrid systems.
