logical scalability

The computational self-awareness of agents, particularly in their design and execution of workflows, empowers entities to construct workflows, or logical frameworks, within the network in a distributed manner. Within a decentralized network, meta-agents serve as intermediaries that orchestrate the transformation of input data into output data by curating the computational services of other agents. This culminates in a logical framework comprised of diverse agents interconnected within a networked workflow. While meta-agents operate under the same abstraction as other network agents, internally they maintain only the computational representation of a workflow, encompassing agent identities, inputs and outputs, costs, locations, offered data, as well as scheduling information essential for workflow design and execution.

Upon complete mapping of the computational reflection by a meta-agent, the workflow can be executed autonomously, provided that the initial data and sufficient tokens to cover the costs of all computational agents within the workflow are available. Notably, as meta-agents have the capacity to design workflows involving other computational agents, they themselves can be integrated into higher-level workflows, thereby fostering the network's logical scalability. Meta-agents can construct intricate computational reflections comprising a hierarchy of sub-meta agents, extending down to basic agent services, which continually adapt their costs, workflows, and services offered. Moreover, these workflows can be devised by a human operator, automated process, or AI agent using a consistent level of abstraction. These capabilities will give rise to what we term a decentralized network of dynamic service meshes.