Abstract not found

Abstract There has been substantial work developing simple, efficient no-regret algorithms for a wideclass of repeated decision-making problems including online routing. These are adaptive strategies an individual can use that give strong guarantees on performance even in adversarially-changing environments. There has also been substantial work on analyzing properties of Nash equilibria in routing games. In this paper, we consider the question: if each player in a rout-ing game uses a no-regret strategy, will behavior converge to a Nash equilibrium? In general games the answer to this question is known to be no in a strong sense, but routing games havesubstantially more structure. In this paper we show that in the Wardrop setting of multicommodity flow and infinitesimalagents, behavior will approach Nash equilibrium (formally, on most days, the cost of the flow will be close to the cost of the cheapest paths possible given that flow) at a rate that dependspolynomially on the players ' regret bounds and the maximum slope of any latency function. We also show that price-of-anarchy results may be applied to these approximate equilibria, and alsoconsider the finite-size (non-infinitesimal) load-balancing model of Azar [2].

Abstract. We study a finite population of mobiles communicating using the slotted ALOHA-type protocol. Our objective is the study of coordination between the mobiles in both cooperative as well as non-cooperative scenarios. Our study is based on the correlated equilibrium concept, a notion introduced by Aumann that broadens the Nash equilibrium. We study ways in which signaling can improve the performance both in the cooperative as well as in the non-cooperative cases, even in the absence of any extra information being conveyed through these signals. 1

cellular networks

Network equilibrium models for that have traditionally been used for transportation planning have penetrated in recent years to other scientific fields. These models have recently been introduced in telecommunications networks literature, as well as in the in the field of game theory. Researchers in the latter fields are not always aware of the very rich literature on equilibrium models outside of their application area. On the other hand, researchers that have used network equilibrium models in transportation may not be aware of new application areas of their tools. The aim of this paper is to present some central research issues and tools in network equilibria and pricing that could bring closer the three mentioned research communities.

We consider the following belief free solution concepts for games with incomplete information: (i) incomplete information rationalizability, (ii) incomplete information correlated equilibrium and (iii) ex post equilibrium. We present epistemic foundations for these solution concepts and establish relationships between them. The properties of these solution concepts are further developed in supermodular games and potential games.

Optimism-bias is inconsistent with the independence of decision weights and payoffs found in models of choice under risk, such as expected utility theory and prospect theory. Hence, to explain the evidence suggesting that agents are optimistically biased, we propose an alternative model of risky choice, affective decision-making, where decision weights — which we label affective or perceived risk — are endogenized. Affective decision making (ADM) is a strategic model of choice under risk, where we posit two cognitive processes: the “rational” and the “emotional” processes. The two processes interact in a simultaneous-move intrapersonal potential game, and observed choice is the result of a pure strategy Nash equilibrium in this potential game. We show that regular ADM potential games have an odd number of locally unique pure strategy Nash equilibria, and demonstrate this …nding for a¤ective decision making in insurance markets. We prove that ADM potential games are refutable, by axiomatizing the ADM potential maximizers.

We study power control in a multi-cell CDMA wireless system whereby self-interested users share a common spectrum and interfere with each other. Our objective is to design a power control scheme that achieves a (near) optimal power allocation with respect to any predetermined network objective (such as the maximization of sum-rate, or some fairness criterion). To obtain this, we introduce the potentialgame approach that relies on approximating the underlying noncooperative game with a “close ” potential game, for which prices that induce an optimal power allocation can be derived. We use the proximity of the original game with the approximate game to establish through Lyapunov-based analysis that natural userupdate schemes (applied to the original game) converge within a neighborhood of the desired operating point, thereby inducing near-optimal performance in a dynamical sense. Additionally, we demonstrate through simulations that the actual performance can in practice be very close to optimal, even when the approximation is inaccurate. As a concrete example, we focus on the sumrate objective, and evaluate our approach both theoretically and empirically.

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Affective decision-making is a strategic model of choice under risk and uncertainty where we posit two cognitive processes — the "rational " and the "emotional" process. Observed choice is the result of equilibirum in this intrapersonal game. As an example, we present applications of affective decision-making in insurance markets, where the risk perceptions of consumers are endogenous. We then derive the axiomatic foundation of affective decision making, and show that, although beliefs are endogenous, not every pattern of behavior is possible under affective decision making.