Understanding collective behavior in nature and its potential links to the engineering of collective artificial behavior attracts many researchers from biology, computer science, and swarm robotics. It impacts different scientific and industrial topics such as cell-biology, cancer study, environment cleaning, swarms of drones, unmanned robots, and more generally collective adaptive systems based on IoT or massive ICT deployment. For instance, cancer cells exhibit collective behaviors, bio-medicine researchers look for different examples from nature to design anti-cancer drugs to shrink tumors in human bodies. An interesting form of collective system is demonstrated by Dictyostelium discoideum and its multicellular development process. D. discoideum1 is a social amoeba able to change its behavior to survive in response to nutrient starvation. Most of its life, the organism lives in the soil as a single amoeba and feeds on bacteria. Individual cells move around on their own when there is plenty of food. Then, when food is scarce, the cells start a multicellular developmental process. Up to a million amoeboid cells artfully self-aggregate via pattern formation (first-order emergent behavior) to build a coherent and cohesive super-organism, similar to a motile slug structure. This complex super-organism has several properties that none of the cells has on its own (e.g. sensitivity to light and heat). The slug moves as a whole (second-order emergent behavior) looking for a suitable place to transform into a fruiting body in which about 20% of the cells die to lift the remaining cells up to a better place for sporulation and dispersal on the surface of the soil [12].