227 research outputs found
On Blockchain We Cooperate: An Evolutionary Game Perspective
Cooperation is fundamental for human prosperity. Blockchain, as a trust
machine, is a cooperative institution in cyberspace that supports cooperation
through distributed trust with consensus protocols. While studies in computer
science focus on fault tolerance problems with consensus algorithms, economic
research utilizes incentive designs to analyze agent behaviors. To achieve
cooperation on blockchains, emerging interdisciplinary research introduces
rationality and game-theoretical solution concepts to study the equilibrium
outcomes of various consensus protocols. However, existing studies do not
consider the possibility for agents to learn from historical observations.
Therefore, we abstract a general consensus protocol as a dynamic game
environment, apply a solution concept of bounded rationality to model agent
behavior, and resolve the initial conditions for three different stable
equilibria. In our game, agents imitatively learn the global history in an
evolutionary process toward equilibria, for which we evaluate the outcomes from
both computing and economic perspectives in terms of safety, liveness,
validity, and social welfare. Our research contributes to the literature across
disciplines, including distributed consensus in computer science, game theory
in economics on blockchain consensus, evolutionary game theory at the
intersection of biology and economics, bounded rationality at the interplay
between psychology and economics, and cooperative AI with joint insights into
computing and social science. Finally, we discuss that future protocol design
can better achieve the most desired outcomes of our honest stable equilibria by
increasing the reward-punishment ratio and lowering both the cost-punishment
ratio and the pivotality rate
Many-agent Reinforcement Learning
Multi-agent reinforcement learning (RL) solves the problem of how each agent should behave optimally in a stochastic environment in which multiple agents are learning simultaneously. It is an interdisciplinary domain with a long history that lies in the joint area of psychology, control theory, game theory, reinforcement learning, and deep learning. Following the remarkable success of the AlphaGO series in single-agent RL, 2019 was a booming year that witnessed significant advances in multi-agent RL techniques; impressive breakthroughs have been made on developing AIs that outperform humans on many challenging tasks, especially multi-player video games. Nonetheless, one of the key challenges of multi-agent RL techniques is the scalability; it is still non-trivial to design efficient learning algorithms that can solve tasks including far more than two agents (), which I name by \emph{many-agent reinforcement learning} (MARL\footnote{I use the world of ``MARL" to denote multi-agent reinforcement learning with a particular focus on the cases of many agents; otherwise, it is denoted as ``Multi-Agent RL" by default.}) problems. In this thesis, I contribute to tackling MARL problems from four aspects. Firstly, I offer a self-contained overview of multi-agent RL techniques from a game-theoretical perspective. This overview fills the research gap that most of the existing work either fails to cover the recent advances since 2010 or does not pay adequate attention to game theory, which I believe is the cornerstone to solving many-agent learning problems. Secondly, I develop a tractable policy evaluation algorithm -- -Rank -- in many-agent systems. The critical advantage of -Rank is that it can compute the solution concept of -Rank tractably in multi-player general-sum games with no need to store the entire pay-off matrix. This is in contrast to classic solution concepts such as Nash equilibrium which is known to be -hard in even two-player cases. -Rank allows us, for the first time, to practically conduct large-scale multi-agent evaluations. Thirdly, I introduce a scalable policy learning algorithm -- mean-field MARL -- in many-agent systems. The mean-field MARL method takes advantage of the mean-field approximation from physics, and it is the first provably convergent algorithm that tries to break the curse of dimensionality for MARL tasks. With the proposed algorithm, I report the first result of solving the Ising model and multi-agent battle games through a MARL approach. Fourthly, I investigate the many-agent learning problem in open-ended meta-games (i.e., the game of a game in the policy space). Specifically, I focus on modelling the behavioural diversity in meta-games, and developing algorithms that guarantee to enlarge diversity during training. The proposed metric based on determinantal point processes serves as the first mathematically rigorous definition for diversity. Importantly, the diversity-aware learning algorithms beat the existing state-of-the-art game solvers in terms of exploitability by a large margin. On top of the algorithmic developments, I also contribute two real-world applications of MARL techniques. Specifically, I demonstrate the great potential of applying MARL to study the emergent population dynamics in nature, and model diverse and realistic interactions in autonomous driving. Both applications embody the prospect that MARL techniques could achieve huge impacts in the real physical world, outside of purely video games
Rational cryptography: novel constructions, automated verification and unified definitions
Rational cryptography has recently emerged as a very promising field of research by combining notions and techniques from cryptography and game theory, because it offers an alternative to the rather inflexible traditional cryptographic model. In contrast to the classical view of cryptography where protocol participants are considered either honest or arbitrarily malicious, rational cryptography models participants as rational players that try to maximize their benefit and thus deviate from the protocol only if they gain an advantage by doing so.
The main research goals for rational cryptography are the design of more efficient protocols when players adhere to a rational model, the design and implementation of automated proofs for rational security notions and the study of the intrinsic connections between game theoretic and cryptographic notions. In this thesis, we address all these issues.
First we present the mathematical model and the design for a new rational file sharing protocol which we call RatFish. Next, we develop a general method for automated verification for rational cryptographic protocols and we show how to apply our technique in order to automatically derive the rational security property for RatFish. Finally, we study the intrinsic connections between game theory and cryptography by defining a new game theoretic notion, which we call game universal implementation, and by showing its equivalence with the notion of weak stand-alone security.Rationale Kryptographie ist kürzlich als ein vielversprechender Bereich der Forschung durch die Kombination von Begriffen und Techniken aus der Kryptographie und der Spieltheorie entstanden, weil es eine Alternative zu dem eher unflexiblen traditionellen kryptographischen Modell bietet. Im Gegensatz zur klassischen Ansicht der Kryptographie, nach der Protokollteilnehmer entweder als ehrlich oder willkürlich bösartig angesehen werden, modelliert rationale Kryptografie die Protokollteilnehmer als rationale Akteure, die versuchen ihren Vorteil zu maximieren und damit nur vom Protokoll abweichen, wenn sie dadurch einen Vorteil erlangen.
Die wichtigsten Forschungsziele rationaler Kryptographie sind: das Design effizienterer Protokolle, wenn die Spieler ein rationale Modell folgen, das Design und die Implementierung von automatisierten Beweisen rationaler Sicherheitsbegriffe und die Untersuchung der intrinsischen Verbindungen zwischen spieltheoretischen und kryptographischen Begriffen. In dieser Arbeit beschäftigen wir uns mit all diesen Fragen.
Zunächst präsentieren wir das mathematische Modell und das Design für RatFish, ein neues rationales Filesharing-Protokoll. Dann entwickeln wir eine allgemeine Methode zur automatischen Verifikation rationaler kryptographischer Protokolle und wir zeigen, wie man unsere Technik nutzen kann, um die rationale Sicherheitseigenschaft von RatFish automatisch abzuleiten. Abschließend untersuchen wir die intrinsische Verbindungen zwischen Spieltheorie und Kryptographie durch die Definition von game universal implementation, einem neuen spieltheoretischen Begriff, und wir zeigen die Äquivalenz von game universal implementation und weak stand-alone security
Three essays on the economics of air transportation
Cette thèse est constituée de trois essais en économie du transport aérien. Le premier essai, intitulé "Effects of Corruption on Efficiency of the European Airports", établit un lien entre la corruption et l’efficacité opérationnelle des aéroports européens. Plusieurs États ont privatisé et commercialisé leurs aéroports publics dans le but d’améliorer l’efficacité de leurs opérations. Cependant, un niveau élevé de corruption dans le pays pourrait compromettre la réalisation de cet objectif. La littérature économique suggère que l’exposition à la corruption peut interférer dans l’allocation des ressources, surtout lorsqu’il s’agit de grandes infrastructures. En utilisant des données sur 47 aéroports européens observés au cours de la période de 2003 à 2009 et un indicateur de corruption provenant de "International Country Risk Guide", nous montrons que la corruption a des effets négatifs sur l’efficacité des aéroports et l’ampleur des impacts dépend des structures de propriété et de gestion des aéroports (public, privé et mixte). En particulier, la corruption réduit l’efficacité des aéroports privés. Ces derniers deviennent même moins efficaces que les aéroports publics lorsque l’environnement est fortement corrompu. Nous concluons que la privatisation n’améliore pas nécessairement la performance des aéroports lorsque la corruption est élevée. Le deuxième essai, intitulé "Flexible Estimation of an Airport Choice Model : The Case of Quebec Airports", analyse les déterminants de choix des voyageurs entre un aéroport régional et une plate-forme de correspondance aéroportuaire au Québec. Parmi les modèles les plus populaires, nous explorons le logit à coefficients fixes et variables, le logit additif généralisé et les estimateurs de probabilités conditionnelles de noyaux pour variables continues et discrètes. Les modèles empiriques utilisent les résultats d’une enquête sur la qualité des services aux aéroports réalisée auprès des passagers embarquant à l’un des deux aéroports principaux de Québec en 2010. Les résultats économétriques soulignent l’importance de la fréquence de vol et de l’accessibilité à l’aéroport dans le choix des voyageurs. Le prix du service, la raison du déplacement ainsi que la destination et l’horaire du vol paraissent aussi pertinents. Bien que les modèles logistiques testés ont des fondements théoriques basés sur les modèles d’utilité aléatoire, les tests économétriques d’adéquation de la forme fonctionnelle rejettent ces modèles. Les estimateurs de noyaux offrent une alternative flexible pour capturer des non-linéarités et des effets d’interaction entre les variables explicatives qui échappent aux modèles logistiques. Le troisième essai, intitulé "When Hotelling Meets Vickrey - Spatial Differentiation and Service Timing in the Airline Industry", développe un modèle de concurrence duopolistique entre deux aéroports desservis chacun par un transporteur. Les transporteurs offrent un seul vol vers une même destination. L’interaction entre les aéroports et les transporteurs est modélisée à l’aide d’un jeu séquentiel à trois étapes. Dans un premier temps, les aéroports fixent (simultanément) la taxe aéroportuaire chargée aux transporteurs et annoncent la plage horaire disponible pour le vol. Ensuite, les transporteurs fixent chacun l’heure de leur vol. À la dernière étape, les transporteurs décident du prix du voyage. Les voyageurs, répartis sur un espace géographique linéaire de taille fixe et dotés de préférences hétérogènes pour les heures de départ, choisissent le couple aéroport-transporteur en fonction du prix du billet d’avion, du coût de déplacement vers les infrastructures et du coût de déshorage (coût monétaire de partir avant ou après l’heure préférée). Ce cadre d’analyse est utilisé pour explorer l’impact de l’emplacement géographique des aéroports et de l’horaire du vol sur les taxes aéroportuaires, les prix du billet d’avion, la demande des voyageurs et les profits. Les résultats montrent qu’un aéroport qui bénéficie d’une meilleure localisation géographique charge une taxe aéroportuaire plus élevée que son concurrent et que son transporteur profite également de cet avantage en localisation pour accroître ses prix vis-à -vis du transporteur concurrent. Lorsque les coûts opérationnels des transporteurs ne dépendent pas de l’heure de départ, ils fixent un horaire identique et la concurrence pour attirer les voyageurs se fait exclusivement par les prix des billets. Si leurs coûts varient selon l’heure de départ, les transporteurs différencient en général leur horaire, et cela même lorsque ces coûts horaires sont identiques entre transporteurs. La différenciation des temps de départ permet aux aéroports et aux transporteurs de se concurrencer en horaire, ce qui peut réduire ou renforcer l’avantage géographique.My thesis is composed of three essays on the economics of air transportation. My first essay, entitled "Effects of Corruption on Efficiency of the European Airports", analyzes the effect of corruption on airport productive efficiency in Europe. Many governments have privatized and commercialized their airports in order to improve efficiency of their operations. However, this objective may not be achieved if the business-operating environment is very corrupt. According to the economics literature, corruption may be a hindrance to efficiency, especially when it comes to large infrastructures. Using an unbalanced panel data of 47 major European airports from 2003 to 2009 and the corruption measure provided by International Country Risk Guide (ICRG), we show that corruption has a negative impact on airport operating efficiency and the effect depends on the ownership form (private, public and mixed). Airports under mixed public-private ownership with private majority achieve lower levels of efficiency when located in more corrupt countries. They even operate less efficiently than fully and/or majority government owned airports in highly corruption environment. We conclude that privatization may not lead to efficiency gains in countries that suffer from higher levels of corruption. My second essay, entitled "Flexible Estimation of an Airport Choice Model: The Case of Quebec airports", explores the determinants of passengers’ choice between a primary hub and a secondary airport in Quebec. Among the most popular models, we explore fixed- and randomcoefficients logistic models along with two flexible alternatives including an additive logistic model and a kernel-based conditional density with continuous and discrete variables. Using an original dataset from the 2010 Airport Service Quality survey conducted in Quebec airports, we show that flight frequency, access time and access mode to airports, among others, are the main factors of airports’ choice across all specifications. Airfare, the reason for travel, flight destination and departure times also appear to have significant impacts. While the logistic models have strong theoretical foundations based on the random utility models, the recent kernel-based tests reject these specifications. The nonparametric kernel estimators provide flexible tools to capture non linearities and interactions effects between selected explanatory variables without imposing shape constraints on the conditional probability. My third essay, entitled "When Hotelling Meets Vickrey - Spatial Differentiation and Service Timing in the Airline Industry", investigates rivalry between transport facilities in a model that includes two sources of horizontal differentiation: geographical location and departure time. We explore how both sources influence facility fees and the price of the service offered by downstream carriers. The interactions between the facilities and their carriers are represented as a sequential three-stage game in fees, departure times and fares with simultaneous choices at each stage. Travellers’ cost includes a fare, a transportation cost to the facility and a schedule delay cost, which captures the monetary cost of departing earlier or later than desired. One carrier operates at each facility and schedules a single departure time. We show that duopolistic competition drives to an identical departure time across carriers when their operational cost does not vary with the time of day, but generally leads to distinct service times when this cost depends on the time of the day. When a facility possesses a location advantage, it can set a higher fee and its downstream carrier can charge a higher fare. Departure time differentiation allows the facilities and their carrier to compete along an additional differentiation dimension that can reduce or strengthen the advantage in location
Essays in financial intermediation and banking
Banks' role as intermediaries between short term investors and long term borrow-
ers has dominated the literature. Whilst this is an important feature, there are many
other characteristics of banks. Each chapter in this PhD explores a different aspect
of banking, from other forms of lending to banks' role in payment services. The first,
and principal, chapter considers credit lines: `commitments' to lend if required. These
remain off the bank's balance sheet until drawn upon. As off-balance sheet items,
unused commitments face low capital charges under existing capital regulation. I ex-
plore how this regulatory feature incentivises banks to build up exposure to these lines.
This may lead to a suboptimal allocation of credit, ex post, following a market shock,
as high drawdowns cause the balance sheet to balloon and the capital requirement
to bind. In the second chapter, I consider banks as agents in large-value payment
systems. In choosing the optimal time to settle a payment, banks trade off delay costs
against the risk of having insuffcient liquidity to make future payments. With banks
participating in multiple systems, I show how default in one system may spill over into
another, through the strategic behaviour of multi-system participants. I explore how
this risk varies with the degree of information asymmetry between agents in different
systems. The third chapter focuses on retail banking. In joint work, we examine how
the provision of consumer credit, either through current account overdrafts, or through
credit card credit lines, affects the way in which debit and credit card networks com-
pete. We find that, even when debit and credit cards compete, there are elements
of complementarity between them. Banks providing debit cards and current accounts
benefit when the consumer delays withdrawal of funds from her current account by
using a credit card. This leads to surprisingly high debit merchant fees
Altruistically Inclined?: The Behavioral Sciences, Evolutionary Theory, and the Origins of Reciprocity
Altruistically Inclined? examines the implications of recent research in the natural sciences for two important social scientific approaches to individual behavior: the economic/rational choice approach and the sociological/anthropological. It considers jointly two controversial and related ideas: the operation of group selection within early human evolutionary processes and the likelihood of modularity—domain-specific adaptations in our cognitive mechanisms and behavioral predispositions.
Experimental research shows that people will often cooperate in one-shot prisoner\u27s dilemma (PD) games and reject positive offers in ultimatum games, contradicting commonly accepted notions of rationality. Upon first appearance, predispositions to behave in this fashion could not have been favored by natural selection operating only at the level of the individual organism.
Emphasizing universal and variable features of human culture, developing research on how the brain functions, and refinements of thinking about levels of selection in evolutionary processes, Alexander J. Field argues that humans are born with the rudiments of a PD solution module—and differentially prepared to learn norms supportive of it. His emphasis on failure to harm, as opposed to the provision of affirmative assistance, as the empirically dominant form of altruistic behavior is also novel.
The point of departure and principal point of reference is economics. But Altruistically Inclined? will interest a broad range of scholars in the social and behavioral sciences, natural scientists concerned with the implications of research and debates within their fields for the conduct of work elsewhere, and educated lay readers curious about essential features of human nature.https://scholarcommons.scu.edu/faculty_books/1325/thumbnail.jp
Game Theory
This is a two-volume set that provides an introduction to non-cooperative Game Theory. Volume 1 covers the basic concepts, while Volume 2 is devoted to advanced topics.
The book is richly illustrated with approximately 400 figures. It is suitable for both self-study and as the basis for an undergraduate course in game theory as well as a first-year graduate-level class. It is written to be accessible to anybody with high-school level knowledge of mathematics. At the end of each chapter there is a collection of exercises accompanied by detailed answers. The book contains approximately 180 exercises
Game Theory (Open Access textbook with 165 solved exercises)
This is an Open Access textbook on non-cooperative Game Theory with 165
solved exercises.Comment: 578 pages, 163 figure
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