Node-Max-Cut and the Complexity of Equilibrium in Linear Weighted Congestion Games

In this work, we seek a more refined understanding of the complexity of local optimum computation for Max-Cut and pure Nash equilibrium (PNE) computation for congestion games with weighted players and linear latency functions. We show that computing a PNE of linear weighted congestion games is PLS-complete either for very restricted strategy spaces, namely when player strategies are paths on a series-parallel network with a single origin and destination, or for very restricted latency functions, namely when the latency on each resource is equal to the congestion. Our results reveal a remarkable gap regarding the complexity of PNE in congestion games with weighted and unweighted players, since in case of unweighted players, a PNE can be easily computed by either a simple greedy algorithm (for series-parallel networks) or any better response dynamics (when the latency is equal to the congestion). For the latter of the results above, we need to show first that computing a local optimum of a natural restriction of Max-Cut, which we call Node-Max-Cut, is PLS-complete. In Node-Max-Cut, the input graph is vertex-weighted and the weight of each edge is equal to the product of the weights of its endpoints. Due to the very restricted nature of Node-Max-Cut, the reduction requires a careful combination of new gadgets with ideas and techniques from previous work. We also show how to compute efficiently a (1+?)-approximate equilibrium for Node-Max-Cut, if the number of different vertex weights is constant

Leveraging information in vehicular parking games

Our paper approaches the parking assistance service in urban environments as an instance of service provision in non-cooperative network environments. We propose normative abstractions for the way drivers pursue parking space and the way they respond to partial or complete information for parking demand and supply as well as specific pricing policies on public and private parking facilities. The drivers are viewed as strategic agents who make rational decisions attempting to minimize the cost of the acquired parking spot. We formulate the resulting games as resource selection games and derive their equilibria under different expressions of uncertainty about the overall parking demand. The efficiency of the equilibrium states is compared against the optimal assignment that could be determined by a centralized entity and conditions are derived for minimizing the related price of anarchy value. Our results provide useful hints for the pricing and practical management of on-street and private parking resources. More importantly, they exemplify counterintuitive less-is-more effects about the way information availability modulates the service cost, which underpin general competitive service provision settings and contribute to the better understanding of effective information mechanisms

Satellite Networks: Architectures, Applications, and Technologies

Since global satellite networks are moving to the forefront in enhancing the national and global information infrastructures due to communication satellites' unique networking characteristics, a workshop was organized to assess the progress made to date and chart the future. This workshop provided the forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. Presentations on overview, state-of-the-art in research, development, deployment and applications and future trends on satellite networks are assembled

Designing industry structure and regulation under political economy constraints.

This thesis focuses on the political economy of industrial policy as defined by Laffont (2000). In particular we study the effects of political economy constraints on industry design. Our motivation relies on the results of more than 20 years of regulatory reforms, where industries have been reorganised after their initial privatisation and/or restructure. So far, the literature has extensively studied the relationship between political economy and regulation (Levy &; Spiller (1997); Henisz & Benet (2003)). However, the study of the relationship between political economy and industry structure has received less attention. This has happened despite the fact that, as noted by Dana (1993), industry structure and regulation are jointly determined. Our work contributes to the study of the effects of political economy constraints on industry design. At a theoretical level we build on Auriol & Laffont (1992)'s model of regulation by duopoly and on Dana (1993)'s model of regulating multiproduct natural monopolies. We introduce delegation to their problem and we allow for regulatory capture. In the first case we found that under some circumstances capture biases Congress' decision towards a more competitive structure (duopoly) as the optimal response. In the second case, we find that if preventing capture is too costly, industry design favours horizontal separation of the natural monopolies as the optimal response. At an empirical level, we analyse the political economy constraints that led the Mexican government to reform its natural gas industry while keeping natural gas production as a legal monopoly and organising the industry with a dominant integrated incumbent (transmission and retail). This chapter contributes to our research by opening the "black box" of the determinants of industry design a little more. It also contributes to the literature that has studied Mexican natural gas reform. This literature has concentrated its attention on the study of regulatory incentives, taking industry structure as given

Constructivist and Ecological Rationality in Economics

When we leave our closet, and engage in the common affairs of life, (reason's) conclusions seem to vanish, like the phantoms of the night on the appearance of the morning; and 'tis difficult for us to retain even that conviction, which we had attained with difficulty (Hume, 1739/, p 507). we must constantly adjust our lives, our thoughts and our emotions, in order to live simultaneously within different kinds of orders according to different rules. If we were to apply the unmodified, uncurbed rules (of caring intervention to do visible 'good') of the small band or troop, or our families to the (extended order of cooperation through markets), as our instincts and sentimental yearnings often make us wish to do, we would destroy it. Yet if we were to always apply the (noncooperative) rules of the extended order to our more intimate groupings, we would crush them. (Hayek, 1988, p 18). (Italics are his, parenthetical reductions are mine).behavioral economics; experimental economics

Maximizing Social Welfare and Agreement via Information Design in Linear-Quadratic-Gaussian Games

We consider linear-quadratic Gaussian (LQG) games in which players have quadratic payoffs that depend on the players' actions and an unknown payoff-relevant state, and signals on the state that follow a Gaussian distribution conditional on the state realization. An information designer decides the fidelity of information revealed to the players in order to maximize the social welfare of the players or reduce the disagreement among players' actions. Leveraging the semi-definiteness of the information design problem, we derive analytical solutions for these objectives under specific LQG games. We show that full information disclosure maximizes social welfare when there is a common payoff-relevant state, when there is strategic substitutability in the actions of players, or when the signals are public. Numerical results show that as strategic substitution increases, the value of the information disclosure increases. When the objective is to induce conformity among players' actions, hiding information is optimal. Lastly, we consider the information design objective that is a weighted combination of social welfare and cohesiveness of players' actions. We obtain an interval for the weights where full information disclosure is optimal under public signals for games with strategic substitutability. Numerical solutions show that the actual interval where full information disclosure is optimal gets close to the analytical interval obtained as substitution increases

Market Design for the Transition to Renewable Electricity Systems

The research carried out in this thesis aims to shed light on the role of the European electricity market design in the transition to a target electricity system that combines sustainability, affordability, and reliability. While the ongoing expansion of fluctuating renewable electricity sources challenges the established structures and market mechanisms, governments across Europe have decided to phase-out certain conventional technologies like coal or nuclear power. Since traditional electricity systems rely on flexibility provided by controllable generation capacity, other flexibility options are needed to compensate for the decommissioned conventional power plants and support the system integration of renewables. Against this background, the dissertation extends an established large-scale agent-based electricity market model in order to account for the developments towards an integrated European electricity market and the characteristics of storage technologies. In particular, the representation of cross-border effects is enhanced by integrating approaches from the fields of operations research, non-cooperative game theory, and artificial intelligence in the simulation framework. The extended model is then applied in three case studies to analyze the diffusion of different flexibility options under varying regulatory settings. These case studies cover some central aspects of the European electricity market, most importantly capacity remuneration mechanisms, the interaction of day-ahead market and congestion management, and the role of regulation for residential self-consumption. Results of the case studies confirm that by designing the regulatory framework, policymakers and regulators can substantially affect quantity, composition, location, and operation of technologies – both, on the supply side and the demand side. At the same time, changes and amendments to market design are frequent and will continue to be so in the years ahead. Moreover, given the increasing level of market integration in Europe, the role of cross-border effects of national market designs will gain further in importance. In this context, agent-based simulation models are a valuable tool to better understand potential long-term effects of market designs in the interconnected European electricity system and can therefore support the European energy transition

Multi-agent network games with applications in smart electric mobility

The growing complexity and globalization of modern society brought to light novel problems and challenges for researchers that aim to model real-life phenomena. Nowadays communities and even single individuals cannot be considered as a closed system, since one's actions create a ripple effect that ends up influencing the action of others. Therefore, the study of decision-making processes over networks became a pivotal topic in the research community. The possible applications are virtually endless and span into many different fields. Two of the most relevant examples are smart mobility and energy management in highly populated cities, where a collection of (partially) noncooperative individuals interact over a network trying to reach an efficient equilibrium point, in the sense of Nash, and share limited resources due to the environment in which they operate. In this work, we approach these problems through the lens of game theory. We use different declinations of this powerful mathematical tool to study several aspects of these themes. We design decentralized iterative algorithms solving generalized network games that generate behavioral rules for the players that, if followed, ensure global convergence. Then, we question the classical assumption of perfect players’ rationality by introducing novel dynamics to model partial rationality and analyzing their properties. We conclude by focusing on the design of optimal policies to regulate smart mobility and energy management. In this case, we create a detailed and more realistic description of the problem and use a nudging mechanism, implemented by means of a semi-decentralized algorithm, to align the users' behavior with the one desired by the policymaker

Impacts of survey design and model specification on willingness-to-pay estimates from discrete choice models

Discrete choice models infer individuals’ preferences from observed choices. Analysts can thereby contribute to producing more reliable demand forecasts and assess welfare impacts of policy/scenario changes. However, the risk of model misspecification errors may bias parameter estimates and lead to incorrect demand forecasts and policy recommendations. This thesis examines three types of model misspecifications: i) ignoring travel time constraints, ii) measurement error in the income variable, and iii) ignoring the behavioural phenomenon of the zero-price (ZP) effect. We are particularly interested in understanding the policy implications of these misspecifications on the marginal valuation of qualitative variables. Our analyses are relevant to policy makers as these specification errors prevail in some ‘state-of-the-practice’ model representations commonly used in support of cost-benefit analyses. This thesis first examines the issue of ignoring travel time constraints for simple time-cost trade-offs. Analysts may ignore that some alternatives are not available to individuals as the travel times presented could exceed their time allowances for such journey. We find via simulation that the value of travel time (VTT) can be significantly over-estimated when travel time constraints are not accounted for in estimation. More importantly, we identify the confounding issue between travel time constraints and taste heterogeneity. This thesis then turns to the issue of the measurement error in the income variable. We investigate the extent to which the income measure used in the estimation of choice models contributes to the disparity between the cross-sectional and inter-temporal income elasticity of the VTT. We compile various income measures that are varied in terms of the income re-distribution measures and the intra-household budget allocation based on secondary expenditure data. We empirically test the new income measures based on the modelling framework developed for the 2014/15 UK VTT study. Our results indicate that by additionally accounting for social benefits, the cross-sectional income elasticity of VTT approaches unity. This closes the gap between the cross-sectional and inter-temporal income elasticity. We find the behavioural VTTs, which represent the averages of the VTTs estimated from behavioural models across respondents, to be consistent despite the income variations. However, we find that when moving from the stated choice (SC) to the national travel survey to obtain a nationally representative figure for appraisal, appraisal values diverge as per the income variations due to the sampling bias in the income variable in behavioural model. We highlight the requirement for the sampling of the income to be consistent between the estimation and implementation tool. We finally explore the issue of ignoring the ZP effect in choice modelling. ZP effect is a well-established notion in behavioural economics which explains the tendency for individuals to over-react to free alternatives. The lack of attention to the ZP effect in the choice modelling literature is particularly worrying since ‘free’ status quo (SQ) alternatives are at the heart of many SC surveys, especially outside of transport, and form the basis of contrasting the (policy) ‘interventions’. We develop alternative stated survey designs to identify the ZP effect. We find that the observed preference for remaining at the SQ is largely attributed to the ZP effect within our data. We also present experimental design features that allow separation of the ZP effect from the non-linear cost sensitivity. We stress that the prevalence of the ZP effect in observed choice behaviour may introduce bias to the prediction of welfare when the perfect confounding between the ZP and SQ effects is broken. Overall, this thesis highlights the significant bias on WTP estimates that may be caused by ignoring some basic and fundamental misspecification issues. This thesis closes by suggesting some future improvements required to avoid model misspecification issues identified