Algorithmic Governance of Common-Pool Resources

From P2P Foundation
Jump to: navigation, search




"As we saturate our everyday environment with computing and communication technologies, we can increase our capacities for successful collective action if we devise system infrastructures to support self-organization, self-management and pro-social behavior. Elinor Ostrom’s institutional design principles for managing common-pool resources provide a valuable template for designing effective Internet-based applications for algorithmic self-governance."

"Introduction: Resource Allocation in Open Systems

Using a methodology called sociologically inspired computing,[1] researchers are now attempting to solve engineering problems by developing “formal models of social processes.” This entails examining how people behave in similar situations and, informed by a theory of that behavior grounded in the social sciences, developing a formal characterization of the social behavior (based on the theory) using mathematical and/or computational logic. This logical specification then provides the basis for the specification of an algorithmic framework for solving the original problem.

In networks that function as open systems, for example, a significant challenge is how to allocate scarce resources.

This is a vexing challenge because open computing systems and networks are formed on the fly, by mutual agreement, and therefore they may encounter situations at run-time that were not anticipated at design-time. Specific examples include ad hoc networks, sensor networks, opportunistic and vehicular networks, and cloud and grid computing. All these applications have at least one feature in common: the system components (henceforth referred to as agents) must somehow devise a means to collectivize their computing resources (processor time, battery power, memory, etc.) in a common pool, which they can then draw upon in order to achieve their individual goals in a group (or as a group) that they would be unable to do if they each functioned in isolation.

However, open systems face serious challenges in coordinating agents because there is no centralized controller-agent that is compelling other agents in the system to behave in a certain way with regards to the provision and appropriation of resources. Furthermore, all agents may be competing for a larger share of the common pool, and may therefore not comply with the requirements for “correct” (pro-social) behavior. For example, they may appropriate resources that they were not allocated, or they may appropriate resources correctly but fail to contribute expected resources (a phenomenon known as “free riding”)."