Jeu | EPFL Graph Search

thumb|Les Joueurs de cartes de Paul Cézanne (1892-1895, Institut Courtauld). Le jeu est une activité, humaine ou animale, pratiquée pour se divertir. Propre aux mammifères, cette activité d'ordre psychique ou bien physique crée une dépense d'énergie décorrélée des intérêts essentiels immédiats autres que le plaisir. De ce fait, Johan Huizinga remarque que de très nombreuses activités humaines peuvent s'assimiler à des jeux. Mais la définition du jeu reste difficile à circonscrire, ce qui présente un intérêt pour la philosophie. Il est plus facile de répertorier les jeux. Ceux-ci se caractérisent généralement par un nom et des règles qu'on peut classer par types. Les sciences de l'éducation et du développement humain, les sciences cognitives, la pédagogie examinent le jeu comme pratique infantile, importante pour les apprentissages et l'éducation, ce qui peut le rendre productif à moyen et long termes. Dans le jeu, le jeune humain, comme celui d'autres espèces, réalise sans enjeu vi

A simulation and behavioral study of decision and risk in blackjack

The purpose of this master project was to explore decision making process applied to a blackjack game and make the links with facets of impulsivity. The first part of this study goes through the mathematical of this game and presented the optimal policy, computed with reinforcement learning algorithm. We also computed with a Monte Carlo simulation, for each possible hand and for each possible decision, the 3 values

{Q}_{t}

{H}_{t}

and

{h}_{t}

, value function, risk, one-step-ahead risk proposed by d'Acremont & Bossaerts, 2008. The second part of the study present the result of the behavioural study. Forty-seven undergraduate students perform 200 blackjack hands and completed a self-report questionnaire evaluating impulsivity and risk attitude. Our analysis reveals links with lack of perseverance and decision time. Furthermore percentage of optimal decision along the game reveals learning with novice player. The result of this study can be used as a basis for future research in neuroimaging on the risk, to try to answer if is possible to distinguish brain area associated with one-step ahead versus total risk

2009

Cellular Operators in a Shared Spectrum

Sivan Altinakar

Due to the increasing number of radio technologies, the available frequency spectrum becomes more and more utilized, hence its clever use becomes a critical issue. Among many proposed solutions, the formulation of the problem as the control of the power of the base stations, also known as the Power Control problem, seems a promising idea. In the present work, we propose to study this problem by first defining a theoretical model. Then, we design a family of non-cooperative games that hopefully stop at a Nash equilibria close to the optimal solution for the network, as well as a few simple tabu search heuristics. We finally developed a java library and a program, in order to experimentally study the behavior of the proposed games and heuristics.

2006

Multi-Agent Learning for Resource Allocation Problems

Ludek Cigler

We analyze resource allocation problems where N independent agents want to access C resources. Each resource can be only accessed by one agent at a time. In order to use the resources efficiently, the agents need to coordinate their access. We focus on decentralized coordination, i.e. coordination without central authority. We analyze coordination mechanisms for two different kind of agents: 1) cooperative, who follow the prescribed protocol entirely; and 2) non-cooperative, who attempt to maximize their own utility. We propose a novel approach to achieve a fair and efficient resource allocation when the agents are cooperative. The agents access resources in slots. At the beginning of each slot, they observe a global coordination signal – a random integer 1 ≤ k ≤ K . The agents then learn a different allocation for each value of the coordination signal. When modeled as a game, the canonical solution to the resource allocation problem is the correlated equilibrium. In a correlated equilibrium, a “smart” coordination device chooses the actions for the “stupid” agents, who then have no incentive to deviate from these recommendations. In contrast, in our solution the coordination signal is “stupid”, since it is not specific to the game. The agents are “smart”, because they learn their strategy independently for each signal value. We show that our learning algorithm converges to an efficient resource allocation in polynomial time. The resulting allocation becomes more fair as the number of signals K increases. A non-cooperative, self-interested agent can exploit our cooperative allocation scheme by accessing one resource all the time, until everyone else gives up. Therefore, for the non-cooperative agents, we consider an infinitely repeated resource allocation game with discounting. This game is symmetric and all the agents are identical, so we look for its symmetric subgame-perfect equilibria. (Bhaskar (2000)) proposed a solution for 2-agent, 1-resource allocation games: Agents start by symmetrically choosing their actions randomly, and as soon as they each choose different actions, they start to follow a convention that prescribes their actions from then on. We extend the concept of convention to the general resource allocation problems of N agents and C resources. We show that for any convention, there exists a symmetric subgame-perfect equilibrium that implements it. We present two conventions: bourgeois, where agents stick to the first allocation; and market, where agents pay for the use of resources, and observe a global coordination signal that allows them to alternate between different allocations. We define the price of anonymity of a convention as the ratio between the maximum social payoff of any (asymmetric) strategy profile and the expected social payoff of the convention. We show that the price of anonymity of the bourgeois convention is infinite. The market convention decreases this price by reducing the conflict between the agents.

EPFL2013

A simulation and behavioral study of decision and risk in blackjack

{Q}_{t}

{H}_{t}

and

{h}_{t}

2009

Multi-Agent Learning for Resource Allocation Problems

Ludek Cigler

EPFL2013