Legal shifts : shaping expectations of intellectual property protection in an open innovation industrial environment

Projet de recherche réalisé en 2014-2015 avec l'appui du Fonds de recherche du Québec – Société et culture.

Alternating offer games and private rulings of the Australian Tax Office

The concept of submitting oneself to a voluntary negotiation is by no means new to big business. Formal bargaining has been quite successful over the years in providing the venue for agents to explore a more logical and mathematical approach to bargaining. However in more recent times external influences have been applied to agents who provide better deals for favored executives. This external influence has displayed itself in taxtion negotiations to the extent that tax office agents have been dismissed for irresponsible conduct. We explore this specific type of negotiation using an alternating offer bargaining game to model the particular influences, which create unfair rulings in negotiations. By the constraints of this systematic mathematical approach to negotiation, we will explore the advantages of a more formal game theoretic approach. In this presentation we will also elaborate on finding Nash Equilibrium in alternating offer games.

Game-based Approach in e-Learning

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

Quantity-setting games with a dominant firm

We consider a possible game-theoretic foundation of Forchheimer's model of dominant-firm price leadership based on quantity-setting games with one large firm and many small firms. If the large firm is the exogenously given first mover, we obtain Forchheimer's model. We also investigate whether the large firm can emerge as a first mover of a timing game.

Game-Theoretically Allocating Resources to Catch Evaders and Payments to Stabilize Teams

Allocating resources optimally is a nontrivial task, especially when multiple

self-interested agents with conflicting goals are involved. This dissertation

uses techniques from game theory to study two classes of such problems:

allocating resources to catch agents that attempt to evade them, and allocating

payments to agents in a team in order to stabilize it. Besides discussing what

allocations are optimal from various game-theoretic perspectives, we also study

how to efficiently compute them, and if no such algorithms are found, what

computational hardness results can be proved.

The first class of problems is inspired by real-world applications such as the

TOEFL iBT test, course final exams, driver's license tests, and airport security

patrols. We call them test games and security games. This dissertation first

studies test games separately, and then proposes a framework of Catcher-Evader

games (CE games) that generalizes both test games and security games. We show

that the optimal test strategy can be efficiently computed for scored test

games, but it is hard to compute for many binary test games. Optimal Stackelberg

strategies are hard to compute for CE games, but we give an empirically

efficient algorithm for computing their Nash equilibria. We also prove that the

Nash equilibria of a CE game are interchangeable.

The second class of problems involves how to split a reward that is collectively

obtained by a team. For example, how should a startup distribute its shares, and

what salary should an enterprise pay to its employees. Several stability-based

solution concepts in cooperative game theory, such as the core, the least core,

and the nucleolus, are well suited to this purpose when the goal is to avoid

coalitions of agents breaking off. We show that some of these solution concepts

can be justified as the most stable payments under noise. Moreover, by adjusting

the noise models (to be arguably more realistic), we obtain new solution

concepts including the partial nucleolus, the multiplicative least core, and the

multiplicative nucleolus. We then study the computational complexity of those

solution concepts under the constraint of superadditivity. Our result is based

on what we call Small-Issues-Large-Team games and it applies to popular

representation schemes such as MC-nets.

Passivity Framework for Modeling, Composing and Mitigating Cyber Attacks

Thesis (Ph.D.)--University of Washington, 2016-08

Computational Analysis of Intelligent Agents: Social and Strategic Settings

The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.

Developing real option game models

By mixing concepts from both game theoretic analysis and real options theory, an investment decision in a competitive market can be seen as a ‘‘game’’ between firms, as firms implicitly take into account other firms’ reactions to their own investment actions. We review two decades of real option game models, suggesting which critical problems have been ‘‘solved’’ by considering game theory, and which significant problems have not been yet adequately addressed. We provide some insights on the plausible empirical applications, or shortfalls in applications to date, and suggest some promising avenues for future research.

Simulação de Robôs Quadrúpedes Utilizando o SimMechanics

Desde sempre o Homem procurou automatizar tarefas repetitivas. Tanto na indústria como no sector doméstico ou de comércio estão constantemente a surgir novos equipamentos procurando aumentar o nível de automação de diversas tarefas. A necessidade de empresas criadoras de produtos inovadores se manterem concorrenciais obrigou à adopção de métodos de projecto e planeamento mais estruturados e eficientes que eliminem os desperdícios tanto de material como de tempo. Diversas construções em termos orçamentais e o aumento da procura de produtos de alta qualidade a baixo custo deu origem a um novo tipo de programas, os programas de simulação virtual. Tal como na indústria, também na investigação nas Instituições de Ensino Superior se procuram adoptar os métodos de trabalho mais eficientes possíveis. Uma parte dos programas de simulação robótica utilizados hoje em dia na investigação no Instituto Superior de Engenharia do Porto estão concebidos em linguagem C. Embora esta linguagem seja extremamente capaz, existem métodos mais adequados de simulação que aceleram o processo de modelação permitindo a visualização do movimento e simulação de diversas situações potencialmente criticas sem existir a necessidade de construção de um protótipo funcional do robô. Durante o último ano, este projecto permitiu construir um modelo de um robô quadrúpede num programa de simulação virtual chamado Simmechanics™. Embora haja já algum trabalho desenvolvido nesta área, constatou-se que a informação existente possuía algumas lacunas. Com o trabalho desenvolvido preparou-se esta dissertação que pretende clarificar algumas questões que surgem na modelação de um robô. Neste documento explica-se como modelar um robô de corpo flexível, modelar as pernas e as respectivas juntas da anca e do joelho assim como também se apresenta a modelação de um contacto com o solo recorrendo a um modelo descrito na literatura. Este documento foi escrito a pensar no leitor, procurando-se explicar de forma simples mas concisa os diversos passos necessários para construir um modelo virtual de um robô. O autor espera, desta forma, ajudar futuros colegas que pretendam trabalhar com o Simmechanics™ a mais facilmente se integrarem com o programa aumentando desta forma o declive da curva de aprendizagem e permitindo um maior aproveitamento desta ferramenta.

Macroeconomic impacts of politics and policy: Applications to financial and real markets

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

Inovação como fator de competitividade da cadeia de valor da moda

Tese de Doutoramento em Engenharia Têxtil

Collusion in growing and shrinking markets: empirical evidence from experimental duopolies

We study collusive behaviour in experimental duopolies that compete in prices under dynamic demand conditions. In one treatment the demand grows at a constant rate. In the other treatment the demand declines at another constant rate. The rates are chosen so that the evolution of the demand in one case is just the reverse in time than the one for the other case. We use a box-design demand function so that there are no issues of finding and co-ordinating on the collusive price. Contrary to game-theoretic reasoning, our results show that collusion is significantly larger when the demand shrinks than when it grows. We conjecture that the prospect of rapidly declining profit opportunities exerts a disciplining effect on firms that facilitates collusion and discourages deviation.

Do market conditions affect gift exchange? Evidence from experimental markets with excess supply and excess demand

We study whether people's behavior in unbalanced gift exchange markets with repeated interaction are affected by whether they are on the excess supply side or the excess demand side of the market. Our analysis is based on the comparison of behavior between two types of experimental gift exchange markets, which vary only with respect to whether first or second movers are on the long side of the market. The direction of market imbalance could influence subjects' behavior, as second movers (workers) might react differently to favorable actions by first movers (firms) in the two cases. While our data show strong deviations from the standard game-theoretic prediction, we find mainly secondary treatment effects. Wage offers are not higher when there is an excess supply of firms, and workers do not respond more favorably to a given wage when there is an excess supply of labor. The state of competition does not appear to have strong effects in our data. We also present data from single-period sessions that show substantial gift exchange even without repeated interactions.

Efficient Nash Equilibrium under Adverse Selection

This paper revisits the problem of adverse selection in the insurance market of Rothschild and Stiglitz [28]. We propose a simple extension of the game-theoretic structure in Hellwig [14] under which Nash-type strategic interaction between the informed customers and the uninformed firms results always in a particular separating equilibrium. The equilibrium allocation is unique and Pareto-efficient in the interim sense subject to incentive-compatibility and individual rationality. In fact, it is the unique neutral optimum in the sense of Myerson [22].

Consumer Behaviour in a Social Context: Implications for Environmental Policy

In this paper we summarise some of our recent work on consumer behaviour, drawing on recent developments in behavioural economics, in which consumers are embedded in a social context, so their behaviour is shaped by their interactions with other consumers. For the purpose of this paper we also allow consumption to cause environmental damage. Analysing the social context of consumption naturally lends itself to the use of game theoretic tools, and indicates that we seek to develop links between economics and sociology rather than economics and psychology, which has been the more predominant field for work in behavioural economics. We shall be concerned with three sets of issues: conspicuous consumption, consumption norms and altruistic behaviour. Our aim is to show that building links between sociological and economic approaches to the study of consumer behaviour can lead to significant and surprising implications for conventional economic policy prescriptions, especially with respect to environmental policy.