  This paper proposes a simple model to capture the complexity of multi-layer
systems where their constituent layers affect, are affected by, each other. The
physical layer is a circuit composed by a power source and resistors in
parallel. Individual agents can add, remove or keep the resistors they have,
and their decisions aiming at maximising the delivered power - a non-linear
function dependent on the others' behaviour - based on their internal state,
their global state perception, the information received from their neighbours
in the communication network, and a randomised selfishness. We develop an
agent-based simulation to analyse the effects of number of agents (size of the
system), communication network topology, communication errors and the minimum
power gain that triggers a behavioural change. Our results show that a
wave-like behaviour at macro-level (caused by individual changes in the
decision layer) can only emerge for a specific system size, the ratio between
cooperators and defectors depends on minimum gain assumed - lower minimal gains
lead to less cooperation and vice-versa, different communication network
topologies lead to different levels of power utilisation and fairness at the
physical layer, and a certain level of error in the communication layer leads
to more cooperation.
