19,980 research outputs found
Multiagent Maximum Coverage Problems: The Trade-off Between Anarchy and Stability
The price of anarchy and price of stability are three well-studied
performance metrics that seek to characterize the inefficiency of equilibria in
distributed systems. The distinction between these two performance metrics
centers on the equilibria that they focus on: the price of anarchy
characterizes the quality of the worst-performing equilibria, while the price
of stability characterizes the quality of the best-performing equilibria. While
much of the literature focuses on these metrics from an analysis perspective,
in this work we consider these performance metrics from a design perspective.
Specifically, we focus on the setting where a system operator is tasked with
designing local utility functions to optimize these performance metrics in a
class of games termed covering games. Our main result characterizes a
fundamental trade-off between the price of anarchy and price of stability in
the form of a fully explicit Pareto frontier. Within this setup, optimizing the
price of anarchy comes directly at the expense of the price of stability (and
vice versa). Our second results demonstrates how a system-operator could
incorporate an additional piece of system-level information into the design of
the agents' utility functions to breach these limitations and improve the
system's performance. This valuable piece of system-level information pertains
to the performance of worst performing agent in the system.Comment: 14 pages, 4 figure
Social Data Offloading in D2D-Enhanced Cellular Networks by Network Formation Games
Recently, cellular networks are severely overloaded by social-based services,
such as YouTube, Facebook and Twitter, in which thousands of clients subscribe
a common content provider (e.g., a popular singer) and download his/her content
updates all the time. Offloading such traffic through complementary networks,
such as a delay tolerant network formed by device-to-device (D2D)
communications between mobile subscribers, is a promising solution to reduce
the cellular burdens. In the existing solutions, mobile users are assumed to be
volunteers who selfishlessly deliver the content to every other user in
proximity while moving. However, practical users are selfish and they will
evaluate their individual payoffs in the D2D sharing process, which may highly
influence the network performance compared to the case of selfishless users. In
this paper, we take user selfishness into consideration and propose a network
formation game to capture the dynamic characteristics of selfish behaviors. In
the proposed game, we provide the utility function of each user and specify the
conditions under which the subscribers are guaranteed to converge to a stable
network. Then, we propose a practical network formation algorithm in which the
users can decide their D2D sharing strategies based on their historical
records. Simulation results show that user selfishness can highly degrade the
efficiency of data offloading, compared with ideal volunteer users. Also, the
decrease caused by user selfishness can be highly affected by the cost ratio
between the cellular transmission and D2D transmission, the access delays, and
mobility patterns
Informative Voting and the Samuelson Rule
We study the classical free-rider problem in public goods provision in a large economy with uncertainty about the average valuation of the public good. Individual preferences over public goods are shaped by a skill and a taste parameter. We use a mechanism design approach to solve for the optimal utilitarian provision rule. The relevant incentive constraints for information aggregation ensure that individuals behave as if they were engaging in informative voting over the level of public good provision. It is shown that the use of information by an optimal provision rule is inversely related to the polarization of preferences which results from the properties of the skill distribution
Endowment additivity and the weighted proportional rules for adjudicating conflicting claims
We propose and study a new axiom, restricted endowment additivity, for the problem of adjudicating conflicting claims. This axiom requires that awards be additively decomposable with respect to the endowment whenever no agentâs claim is filled. For two-claimant problems, restricted endowment additivity essentially characterizes weighted extensions of the proportional rule. With additional agents, however, the axiom is satisfied by a great variety of rules. Further imposing versions of continuity and consistency, we characterize a new family of rules which generalize the proportional rule. Defined by a priority relation and a weighting function, each rule aims, as nearly as possible, to assign awards within each priority class in proportion to these weights. We also identify important subfamilies and obtain new characterizations of the constrained equal awards and proportional rules based on restricted endowment additivity
Quantum Probabilities as Behavioral Probabilities
We demonstrate that behavioral probabilities of human decision makers share
many common features with quantum probabilities. This does not imply that
humans are some quantum objects, but just shows that the mathematics of quantum
theory is applicable to the description of human decision making. The
applicability of quantum rules for describing decision making is connected with
the nontrivial process of making decisions in the case of composite prospects
under uncertainty. Such a process involves deliberations of a decision maker
when making a choice. In addition to the evaluation of the utilities of
considered prospects, real decision makers also appreciate their respective
attractiveness. Therefore, human choice is not based solely on the utility of
prospects, but includes the necessity of resolving the utility-attraction
duality. In order to justify that human consciousness really functions
similarly to the rules of quantum theory, we develop an approach defining human
behavioral probabilities as the probabilities determined by quantum rules. We
show that quantum behavioral probabilities of humans not merely explain
qualitatively how human decisions are made, but they predict quantitative
values of the behavioral probabilities. Analyzing a large set of empirical
data, we find good quantitative agreement between theoretical predictions and
observed experimental data.Comment: Latex file, 32 page
The self-organization of combinatoriality and phonotactics in vocalization systems
This paper shows how a society of agents can self-organize a shared vocalization system that is
discrete, combinatorial and has a form of primitive phonotactics, starting from holistic inarticulate
vocalizations. The originality of the system is that: (1) it does not include any explicit pressure for
communication; (2) agents do not possess capabilities of coordinated interactions, in particular they
do not play language games; (3) agents possess no specific linguistic capacities; and (4) initially
there exists no convention that agents can use. As a consequence, the system shows how a primitive
speech code may bootstrap in the absence of a communication system between agents, i.e. before the
appearance of language
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