UCLA

Socio-technical networks (e.g. social networking services, peer-to-peer systems, etc.) provide a popular, cost-effective and scalable framework for sharing user-generated resources or services. Achieving resource sharing efficiency in socio-technical networks is a challenging problem, because the information available about the various resources is decentralized and it is changing dynamically; the agents may be heterogeneous and have different learning abilities; the agents may make proactive decisions on link formation; and most importantly, the agents may be self-interested, i.e. they take actions which maximize their individual utilities rather than the collective social welfare and thus choose to free-ride rather than share their resources.

The overarching goal of my dissertation is to develop a rigorous and unified paradigm for the joint design of efficient incentive mechanisms and resource management schemes in socio-technical networks. It can be generally divided into two parts.

The first part focuses on the efficient resource sharing in socio-technical networks. Existing distributed network optimization techniques that enable efficient resource allocation when agents are obedient or cooperative are no longer suitable in socio-technical networks which are formed by self-interested agents. The strategic interactions of such self-interested agents lead in numerous socio-technical networks to (Nash) equilibria that are highly inefficient from a social perspective. To achieve social efficiency, incentives need to be provided to agents such that they find in their own self-interest to cooperate and thus act in a socially-optimal way. I propose a general methodology for the design and analysis of rating protocols and associated multi-agent learning algorithms to sustain cooperation in socio-technical networks. Under a rating protocol, an agent is rated based on its behavior. The rating affects the agent's rewards received in the network, which are typically determined according to a differential resource management scheme: compliant agents receive higher ratings and are rewarded by gaining more access to resources compared to non-compliant agents. This preferential treatment thus provides an incentive for agents to cooperate. I rigorously formalize and study the design of rating protocols to optimize the social resource sharing efficiency while encompassing various unique features of socio-technical networks, including the anonymity of agents, asymmetry of interests between different parties in the network, imperfect monitoring, dynamics in the agent population, and white-washing effects (i.e., an individual agent creating multiple identities in the network).

Different from the first part where the underlying network topology is exogenously determined, the second part of my dissertation augments the proposed rating protocols by investigating the endogenous formation of network topologies by the strategic, self-interested agents who produce, disseminate or collect resources. I propose a novel game-theoretic framework to model and analyze the trade-offs (of each individual agent) between the costs and benefits of producing resources personally and forming links to acquire and disseminate resources. A central point of my analysis, which departs from the existing literature on social network formation, is the assumption that the strategic agents are heterogeneous and that agents value this heterogeneity. The heterogeneity of agents and the ability of agents to strategically produce, disseminate or collect resources have striking consequences on the endogenously emerging topology, which provide important guidelines for the design of effective incentive mechanisms and resource management schemes in endogenous socio-technical networks. I first show that the network topology that emerges (at equilibrium) necessarily displays a core-periphery type: hub agents (at the core of the network) produce most of the resources and also create and maintain links to the agents at the periphery, while spoke agents (at the periphery of the network) derive most of their resources from hub agents, producing little of it themselves. As the population becomes larger, the number of hub agents and the total amount of resources produced grow in proportion to the total population. I then show that the networks that emerge at equilibrium are frequently minimally connected and have short network diameters. These ``scale-free'' conclusions had been conjectured for many networks, such as the ``small-world'' phenomenon in the World-Wide-Web, but not derived in any formal framework, and are in stark contradiction to the ``law of the few'' that had been established in previous work, under the assumption that agents solely benefit by forming links for resource acquisition, while resources are homogeneous and part of the endowment of agents, rather than heterogeneous and produced.