New and Provable Results for Network Inference Problems and Multi-agent Optimization Algorithms

abstract: Our ability to understand networks is important to many applications, from the analysis and modeling of biological networks to analyzing social networks. Unveiling network dynamics allows us to make predictions and decisions. Moreover, network dynamics models have inspired new ideas for computational methods involving multi-agent cooperation, offering effective solutions for optimization tasks. This dissertation presents new theoretical results on network inference and multi-agent optimization, split into two parts - The first part deals with modeling and identification of network dynamics. I study two types of network dynamics arising from social and gene networks. Based on the network dynamics, the proposed network identification method works like a `network RADAR', meaning that interaction strengths between agents are inferred by injecting `signal' into the network and observing the resultant reverberation. In social networks, this is accomplished by stubborn agents whose opinions do not change throughout a discussion. In gene networks, genes are suppressed to create desired perturbations. The steady-states under these perturbations are characterized. In contrast to the common assumption of full rank input, I take a laxer assumption where low-rank input is used, to better model the empirical network data. Importantly, a network is proven to be identifiable from low rank data of rank that grows proportional to the network's sparsity. The proposed method is applied to synthetic and empirical data, and is shown to offer superior performance compared to prior work. The second part is concerned with algorithms on networks. I develop three consensus-based algorithms for multi-agent optimization. The first method is a decentralized Frank-Wolfe (DeFW) algorithm. The main advantage of DeFW lies on its projection-free nature, where we can replace the costly projection step in traditional algorithms by a low-cost linear optimization step. I prove the convergence rates of DeFW for convex and non-convex problems. I also develop two consensus-based alternating optimization algorithms --- one for least square problems and one for non-convex problems. These algorithms exploit the problem structure for faster convergence and their efficacy is demonstrated by numerical simulations. I conclude this dissertation by describing future research directions.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Opinion Formation and Herding in Financial Markets

In financial markets, every investor seeks and receives information to decide how they should act (e.g., buy or sell a certain asset). In certain social circles, investors also learn about the decisions of other investors and they might sometimes ignore their own information and take the same decisions as other investors. This phenomenon is known as ”herding effect”. Many believe that herding can be one of the main causes of crashes and bubbles in financial markets.In this thesis, we adopt empirical methods to explore why investors try to imitate others, the impact of herding on financial markets and whether the trading mechanism used in the market affects herding.Towards this goal, we connect opinion formation dynamics with herding in financial markets. We model social connections between the traders in different market environment as a graph and adopt a well-established opinion diffusion dynamics. Opinions are translated to trading positions and market prices evolve accordingly. We relate the shape of the graph social network to the equilibria of a game defined as follows. The players are traders that can strategically decide whether to follow the wisdom of the crowd or act upon their own beliefs.Their payoffs are defined as the wealth they accumulate from trading. We adopt Empirical Game-Theoretic Analysis (EGTA) to compute the equilibria of our games.We first explore the impact of social connections between market participants on herding and market stability in a hypothetical market environment, where orders are always executed at the desired price. We show that the larger the traders’ neighbourhood in the social network, the more the traders are willing to imitate others and the less volatile the stock price is. However, when every trader in the market has perfect knowledge of the opinions of all the other traders, the market will still exhibit crashes and bubbles. The definitions of crashes and bubbles in our research are based on changes in stock prices and are inspired by the financial concept of Maximum Drawdown.The mechanics of trading in an order-driven market environment can influence the behaviour of traders and the idealised setting in our simulated market environment is too simplistic to model real markets. We then investigate opinion formation and herding in order-driven financial markets, which are widely used for many asset classes. We concentrate on Continuous Double Auctions, the principle trading mechanism in this class, and consider two forms of order queuing mechanisms: price-time priority, the de-facto standard, and spread-price/time priority, an alternative recently defined in literature to reduce toxic order flows due to latency arms race. We find that our conclusions are robust and hold in both these realistic market environments; the stronger the social connections between the agents, the more pronounced the herding. Furthermore, our empirical research shows that as the market gives more weight to spread, it becomes more stable thus confirming the findings of related work in our setup.We conclude our work by enlarging the set of strategies that agents use. We use a meta-game to simplify the actual large game and explore herding of different types of investors in the market with different social connections. The results show that the herding is more pronounced among long-term investors than short-term investors. We see our work as the introduction of a framework that can be used to study more questions about herding in financial markets and other complex systems

Exploring the Role of Social Media and Individual Behaviors in Flood Evacuation Processes: An Agent-Based Modeling Approach

Flood warnings from various information sources are important for individuals to make evacuation decisions during a flood event. In this study, we develop a general opinion dynamics model to simulate how individuals update their flood hazard awareness when exposed to multiple information sources, including global broadcast, social media, and observations of neighbors' actions. The opinion dynamics model is coupled with a traffic model to simulate the evacuation processes of a residential community with a given transportation network. Through various scenarios, we investigate how social media affect the opinion dynamics and evacuation processes. We find that stronger social media can make evacuation processes more sensitive to the change of global broadcast and neighbor observations, and thus, impose larger uncertainty on evacuation rates (i.e., a large range of evacuation rates corresponding to sources of information). For instance, evacuation rates are lower when social media become more influential and individuals have less trust in global broadcast. Stubborn individuals can significantly affect the opinion dynamics and reduce evacuation rates. In addition, evacuation rates respond to the percentage of stubborn agents in a nonlinear manner, i.e., above a threshold, the impact of stubborn agents will be intensified by stronger social media. These results highlight the role of social media in flood evacuation processes and the need to monitor social media so that misinformation can be corrected in a timely manner. The joint impacts of social media, quality of flood warnings, and transportation capacity on evacuation rates are also discussed.Additional support was provided by Shenzhen Municipal Science and Technology Innovation Committee (#ZDSY20150831141712549)

The Need for Residential Tenancy Databases in Nigeria

Bad tenants can be a real problem for not paying rent on time or leaving properties in a mess. Lodged information about bad tenants in tenancy databases assists estate agents and landlords make more informed decisions. The study examines the need for residential tenancy databases in Nigeria. Often times, details on a tenancy application form may not be enough to make an informed decision about whether or not the applicant will be a good tenant. The study employed study focus groups using semi-structured face-to-face interviews to gather data among ten principals of estate surveying and valuation firms in Ikeja, Lagos on the one hand; ten prominent local estate agents; five prominent practicing lawyers, ten landlords of multi-tenanted properties and forty tenants within Baruwa/Ipaja neighbourhood in Alimosho Local Government Council area of Lagos State, on the other hand through purposive sampling method. The survey was carried out between September and December, 2013. Data were analysed using tables, percentages and ranking. The study showed that landlords, estate agents and lawyers ranked ability to guide and guard against loss of income to all participants in the real estate business as first and paramount reason for the call for tenancy database. The need to minimize capital loss to landlords was ranked second with ensuring a reduction in overhead expenses by landlords as third. However, public feelings about landlord’s rights on control of building use and character or emotions have no strong weight since for any business venture to be sustainable, a balance of power to a certain level, must exist between the investor and the product consumers

The Need for Residential Tenancy Databases in Nigeria

Bad tenants can be a real problem for not paying rent on time or leaving properties in a mess. Lodged information about bad tenants in tenancy databases assists estate agents and landlords make more informed decisions. The study examines the need for residential tenancy databases in Nigeria. Often times, details on a tenancy application form may not be enough to make an informed decision about whether or not the applicant will be a good tenant. The study employed study focus groups using semi-structured face-to-face interviews to gather data among ten principals of estate surveying and valuation firms in Ikeja, Lagos on the one hand; ten prominent local estate agents; five prominent practicing lawyers, ten landlords of multi-tenanted properties and forty tenants within Baruwa/Ipaja neighbourhood in Alimosho Local Government Council area of Lagos State, on the other hand through purposive sampling method. The survey was carried out between September and December, 2013. Data were analysed using tables, percentages and ranking. The study showed that landlords, estate agents and lawyers ranked ability to guide and guard against loss of income to all participants in the real estate business as first and paramount reason for the call for tenancy database. The need to minimize capital loss to landlords was ranked second with ensuring a reduction in overhead expenses by landlords as third. However, public feelings about landlord’s rights on control of building use and character or emotions have no strong weight since for any business venture to be sustainable, a balance of power to a certain level, must exist between the investor and the product consumers

Realms of Influence: The Dynamics of Social Entrepreneurship in the Kingdom of Jordan

Social enterprises are organizations that employ business-like tactics to achieve primarily social goals, with the distinguishing qualities of having social objectives, using social capital, and creating social value. While there is a body of literature that demonstrates the potential of social entrepreneurship to address various issues in the Middle East, this research instead analyses social enterprises’ actual ability to achieve their goals as independent, community-responsive actors. The work is situated in the wider debates about democratization in the region by assessing the impact that regime surveillance tactics have on the development of social capital. This thesis evaluates social entrepreneurship in its political and legal context and is based on fieldwork in Jordan using semi-structured interviews with social entrepreneurs, members of their support networks, and government officials. By supporting social entrepreneurship, the international community implicitly supports development initiatives that rely on social capital, because social capital is intrinsic to social enterprises. This is problematic because the value of social capital in development is disputed; it can have positive or negative, exclusionary effects. This means that international actors may be supporting a strategy that has been shown to promote only ‘accepted’ kinds of association and perpetuate the status quo. The issue that therefore arises is what the role of social capital is in Jordan, an authoritarian regime where government surveillance is prevalent. This thesis finds that the Jordanian regime uses surveillance and bureaucratic mechanisms to direct and restrict the work of social enterprises by imposing structural restrictions on the development of social capital. Confusing bureaucratic policies, the ministries’ pervasive oversight, restrictions in the legal code, a foreign funding control mechanism, and royal NGOs’ co-optation of social entrepreneurship are all indicators of persisting semi-authoritarian governance approaches. Therefore, Jordan’s social enterprises fail to contribute to the growth of an independent civil society and are not effective development agents due to the many regulatory restrictions that govern them. Through an examination of the impact of the regime’s surveillance on the political liberalization process and the development of social capital, the thesis argues that state support or involvement with social enterprises and social capital can build hierarchical associational relationships instead of social networks that lead to political empowerment. Such social networks have been theorized to lead to mutually beneficial collective action that results in steps towards democratization. In Jordan, however, state surveillance interrupts the pathway from social capital development to democratization. Through the case of social enterprises, the thesis demonstrates that the regime’s interference with social capital negates any theoretical potential it may have to be the ‘building block’ of civil society because it renders social capital the dependent variable. Thus, the state’s influence extends to the very foundations of any democratization processes in Jordan

Assessing the role of human behaviors in the management of extreme hydrological events: an agent-based modeling approach

This thesis aims to assess the role of human behaviors in the management of extreme hydrological events. Using an agent-based modeling (ABM) approach, three specific issues associated with modeling human behaviors are addressed: (1) behavioral heterogeneity, (2) social interaction, and (3) the interplay of multiple behaviors. The modeling approach is applied to two types of extreme hydrological events: floods and droughts. In the case of flood events, an ABM is developed to simulate heterogeneous responses to flood warnings and evacuation decisions. The ABM is coupled with a traffic model to simulate evacuation processes on a transportation network in an impending flood event. Based on this coupled framework, the model further takes account of social interactions, in the form of communication through social media, and evaluates how social interactions affect flood risk awareness and evacuation processes. The case of drought events considers a hypothetical agricultural water market based on double auction. Farmers’ multiple behaviors (irrigation and bidding behaviors) are modeled in an ABM framework. The impacts of the interplay of these behaviors on water market performance are evaluated under various hydrological conditions. The results from the ABMs show that the three aforementioned aspects of human behaviors can significantly affect the effectiveness of the management policies in extreme hydrological events. The thesis highlights the importance of including human behaviors for policy design in flood and drought management. Further, the thesis emphasizes the efforts in collecting empirical data to better represent and simulate human behaviors in coupled human and hydrological systems