259 research outputs found
Collaborative Decision-Making and the k-Strong Price of Anarchy in Common Interest Games
The control of large-scale, multi-agent systems often entails distributing
decision-making across the system components. However, with advances in
communication and computation technologies, we can consider new collaborative
decision-making paradigms that exist somewhere between centralized and
distributed control. In this work, we seek to understand the benefits and costs
of increased collaborative communication in multi-agent systems. We
specifically study this in the context of common interest games in which groups
of up to k agents can coordinate their actions in maximizing the common
objective function. The equilibria that emerge in these systems are the
k-strong Nash equilibria of the common interest game; studying the properties
of these states can provide relevant insights into the efficacy of inter-agent
collaboration. Our contributions come threefold: 1) provide bounds on how well
k-strong Nash equilibria approximate the optimal system welfare, formalized by
the k-strong price of anarchy, 2) study the run-time and transient performance
of collaborative agent-based dynamics, and 3) consider the task of redesigning
objectives for groups of agents which improve system performance. We study
these three facets generally as well as in the context of resource allocation
problems, in which we provide tractable linear programs that give tight bounds
on the k-strong price of anarchy.Comment: arXiv admin note: text overlap with arXiv:2308.0804
Information-Sharing and Privacy in Social Networks
We present a new model for reasoning about the way information is shared
among friends in a social network, and the resulting ways in which it spreads.
Our model formalizes the intuition that revealing personal information in
social settings involves a trade-off between the benefits of sharing
information with friends, and the risks that additional gossiping will
propagate it to people with whom one is not on friendly terms. We study the
behavior of rational agents in such a situation, and we characterize the
existence and computability of stable information-sharing networks, in which
agents do not have an incentive to change the partners with whom they share
information. We analyze the implications of these stable networks for social
welfare, and the resulting fragmentation of the social network
Efficient Equilibria in Polymatrix Coordination Games
We consider polymatrix coordination games with individual preferences where
every player corresponds to a node in a graph who plays with each neighbor a
separate bimatrix game with non-negative symmetric payoffs. In this paper, we
study -approximate -equilibria of these games, i.e., outcomes where
no group of at most players can deviate such that each member increases his
payoff by at least a factor . We prove that for these
games have the finite coalitional improvement property (and thus
-approximate -equilibria exist), while for this
property does not hold. Further, we derive an almost tight bound of
on the price of anarchy, where is the number of
players; in particular, it scales from unbounded for pure Nash equilibria ( to for strong equilibria (). We also settle the complexity
of several problems related to the verification and existence of these
equilibria. Finally, we investigate natural means to reduce the inefficiency of
Nash equilibria. Most promisingly, we show that by fixing the strategies of
players the price of anarchy can be reduced to (and this bound is tight)
Approximate Equilibrium and Incentivizing Social Coordination
We study techniques to incentivize self-interested agents to form socially
desirable solutions in scenarios where they benefit from mutual coordination.
Towards this end, we consider coordination games where agents have different
intrinsic preferences but they stand to gain if others choose the same strategy
as them. For non-trivial versions of our game, stable solutions like Nash
Equilibrium may not exist, or may be socially inefficient even when they do
exist. This motivates us to focus on designing efficient algorithms to compute
(almost) stable solutions like Approximate Equilibrium that can be realized if
agents are provided some additional incentives. Our results apply in many
settings like adoption of new products, project selection, and group formation,
where a central authority can direct agents towards a strategy but agents may
defect if they have better alternatives. We show that for any given instance,
we can either compute a high quality approximate equilibrium or a near-optimal
solution that can be stabilized by providing small payments to some players. We
then generalize our model to encompass situations where player relationships
may exhibit complementarities and present an algorithm to compute an
Approximate Equilibrium whose stability factor is linear in the degree of
complementarity. Our results imply that a little influence is necessary in
order to ensure that selfish players coordinate and form socially efficient
solutions.Comment: A preliminary version of this work will appear in AAAI-14:
Twenty-Eighth Conference on Artificial Intelligenc
Routing Games with Progressive Filling
Max-min fairness (MMF) is a widely known approach to a fair allocation of
bandwidth to each of the users in a network. This allocation can be computed by
uniformly raising the bandwidths of all users without violating capacity
constraints. We consider an extension of these allocations by raising the
bandwidth with arbitrary and not necessarily uniform time-depending velocities
(allocation rates). These allocations are used in a game-theoretic context for
routing choices, which we formalize in progressive filling games (PFGs).
We present a variety of results for equilibria in PFGs. We show that these
games possess pure Nash and strong equilibria. While computation in general is
NP-hard, there are polynomial-time algorithms for prominent classes of
Max-Min-Fair Games (MMFG), including the case when all users have the same
source-destination pair. We characterize prices of anarchy and stability for
pure Nash and strong equilibria in PFGs and MMFGs when players have different
or the same source-destination pairs. In addition, we show that when a designer
can adjust allocation rates, it is possible to design games with optimal strong
equilibria. Some initial results on polynomial-time algorithms in this
direction are also derived
The Present and Future of Game Theory
A broad nontechnical coverage of many of the developments in game theory since the 1950s is given together with some comments on important open problems and where some of the developments may take place. The nearly 90 references given serve only as a minimal guide to the many thousands of books and articles that have been written. The purpose here is to present a broad brush picture of the many areas of study and application that have come into being. The use of deep techniques flourishes best when it stays in touch with application. There is a vital symbiotic relationship between good theory and practice. The breakneck speed of development of game theory calls for an appreciation of both the many realities of conflict, coordination and cooperation and the abstract investigation of all of them.Game theory, Application and theory, Social sciences, Law, Experimental gaming, conflict, Coordination and cooperation
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