Complexity_ A Guided Tour - Melanie Mitchell [85]
In ant colonies, an individual ant samples pheromone signals via its receptors. It bases its decisions on which way to move on the results of these sampled patterns of concentrations of pheromones in its environment. As I described above, individual ants also use sampling of concentration-based information—via random encounters with other ants—to decide when to adopt a particular task. In cellular metabolism, feedback in metabolic pathways arises from bindings between enzymes and particular molecules as enzymes sample spatial and time-varying concentrations of molecules.
Random Components of Behavior
Given the statistical nature of the information read, the actions of the system need to have random (or at least “unpredictable”) components. All three systems described above use randomness and probabilities in essential ways. The receptor shape of each individual lymphocyte has a randomly generated component so as to allow sampling of many possible shapes. The spatial pattern of lymphocytes in the body has a random component due to the distribution of lymphocytes by the bloodstream so as to allow sampling of many possible spatial patterns of antigens. The detailed thresholds for activation of lymphocytes, their actual division rates, and the mutations produced in the offspring all involve random aspects.
Similarly, the movements of ant foragers have random components, and these foragers encounter and are attracted to pheromone trails in a probabilistic way. Ants also task-switch in a probabilistic manner. Biochemist Edward Ziff and science historian Israel Rosenfield describe this reliance on randomness as follows: “Eventually, the ants will have established a detailed map of paths to food sources. An observer might think that the ants are using a map supplied by an intelligent designer of food distribution. However, what appears to be a carefully laid out mapping of pathways to food supplies is really just a consequence of a series of random searches.”
Cellular metabolism relies on random diffusion of molecules and on probabilistic encounters between molecules, with probabilities changing as relative concentrations change in response to activity in the system.
It appears that such intrinsic random and probabilistic elements are needed in order for a comparatively small population of simple components (ants, cells, molecules) to explore an enormously larger space of possibilities, particularly when the information to be gained from such explorations is statistical in nature and there is little a priori knowledge about what will be encountered.
However, randomness must be balanced with determinism: self-regulation in complex adaptive systems continually adjusts probabilities of where the components should move, what actions they should take, and, as a result, how deeply to explore particular pathways in these large spaces.
Fine-Grained Exploration
Many, if not all, complex systems in biology have a fine-grained architecture, in that they consist of large numbers of relatively simple elements that work together in a highly parallel fashion.
Several possible advantages are conferred by this type of architecture, including robustness, efficiency, and evolvability. One additional major advantage is that a fine-grained parallel system is able to carry out what Douglas Hofstadter has called a “parallel terraced scan.” This refers to a simultaneous exploration of many possibilities or pathways, in which the resources given to each exploration at a given time depend on the perceived success of that exploration at that time. The search is parallel in that many different possibilities are explored simultaneously, but is “terraced” in that not all possibilities are explored at the same speeds or to the same depth. Information is used as it is gained to continually