According to Saracco, interactions between various constituents of a Symbiotic Autonomous System (SAS) are also referred to as emergent properties. Thusly, correlation with the environment and other systems is resultant of the emergent properties since they comprise the main attributes of the SAS. In addition, an emergent property is defined as an attribute possessed by the entire system but not its individual components. In this view, the entire system is in charge of making decisions other than a single component being responsible for the processes. Further, the article affirms that a group of autonomous drones can be programmed with vital commands that result in a hierarchy, or they can also be scheduled with rules that in turn influence emergent decisions.
It is worth noting that the above approach is more resilient since the absence of a commander automatically eliminates potential loss. For instance, the internet is a platform that illustrates elaborate administration of packets routing resulting in a highly resilient connectivity system from one users’ to the other (Autonomous decision-making capabilities III). Initially, internet routing procedures such as hot potato routing were reviewed and later implemented as a means to enhance dependability of network connectivity. In recent years, routing procedures have evolved to other variants like mash potato routing, which are particularly structured for autonomous systems.
Further, 5G connectivity at the edges may be perceived as a throng-like infrastructure at the data transfer stage, and is effectively managed without necessarily having an individual entity in charge of routing. Besides, autonomous systems which operate symbiotically necessitate decision-making in the absence of a moderator, and a levelled hierarchy, so as to influence an emergent property from the relationship. Ideally, nature related studies show that such emergent properties resemble those of bees in swarms as well as the decision making processes within one’s brain. Thusly, the comprehension of rudimentary rules which can be coded into an independent autonomous system and its constituents automatically enhances the intuitive decision-making process.
In ‘Advanced Interaction Capabilities VI,’ Saracco affirms that engineers have come up with methodologies that simplify the overall design of a system while enhancing interaction between individual components to attain desired behavior (2017). For instance, within a line of production, robots cooperate with each other to actualize a similar task but such are actually individual goals that have been predefined for the components to coordinate with the system as a whole. In addition, autonomous systems necessitate certain technologies within their design to enhance coordination of individual components.
One technological point of view on autonomous systems is the potential to create a virtual image of the surrounding environment such as in self-driving cars. Besides, the second perspective is the potential for an autonomous system to engage in conversations that are geared towards certain goals in a bid to negotiate certain actions. Alternatively, autonomous systems could take part in mass systems that subscribe to ideally a similar set of rules while establishing a certain context. For instance, such a collaboration is seen in swarms where the foundational technologies are used to program the performance of thousands of mutual autonomous systems (Advanced interaction capabilities IV). In this way, interactions are facilitated by a specified context other than certain entities within that context. Thusly, changes within the behavior of an autonomous system influence contextual changes that have been pointed out by other autonomous systems hence changing their overall behavior. In this way, such sets of local changes generate emergent cooperation. Overall, the article affirms that cooperative technologies are still in development hence over the next few years autonomous systems will have improved interactions amongst themselves.