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.