Many times in both nature and society, distributed elements can synchronize their behavior. This occurs with physical systems such as coupled oscillators, with biological systems such as synchronized firefly flashing and with human systems such as audiences clapping.
Open the Fireflies model from the Biology section of the NetLogo models library. It presents two strategies for fireflies to synchronize their flashes: " phase advance " and " phase delay. "
(a) Change the strategy chooser between " delay " and " advance " while keeping the other settings steady (in particular, keep FLASHES-TO-RESTART at 2). Which strategy seems more effective? Why?
(b) Try adjusting FLASHES-TO-RESTART between 0, 1 and 2 using both phase delay and phase advance settings. Notice that each setting will give a characteristically different plot, and some of them do not allow for synchronization at all (for example, with the delay strategy, contrast FLASHES-TO-RESTART set to 1 as opposed to 2). Why does this control make such a difference in the outcome of the simulation?
(c) This model explores only two general strategies for attaining synchrony in such cycle-governed fireflies. Can you find any others? Can you improve the existing strategies?
(d) There are many other possible situations in which distributed agents must synchronize their behavior through the use of simple rules. What if, instead of perceiving only other discrete flashes, an insect could sense where another insect was in its cycle (perhaps by hearing an increasingly loud hum)? What kinds of strategies for synchronization might be useful in such a situation?
(e) If all fireflies had adjustable cycle-lengths (initially set to random intervals) would it then be possible to coordinate both their cycle-lengths and their flashing?