8,700 research outputs found
The Evolutionary Price of Anarchy: Locally Bounded Agents in a Dynamic Virus Game
The Price of Anarchy (PoA) is a well-established game-theoretic concept to shed light on coordination issues arising in open distributed systems. Leaving agents to selfishly optimize comes with the risk of ending up in sub-optimal states (in terms of performance and/or costs), compared to a centralized system design. However, the PoA relies on strong assumptions about agents\u27 rationality (e.g., resources and information) and interactions, whereas in many distributed systems agents interact locally with bounded resources. They do so repeatedly over time (in contrast to "one-shot games"), and their strategies may evolve.
Using a more realistic evolutionary game model, this paper introduces a realized evolutionary Price of Anarchy (ePoA). The ePoA allows an exploration of equilibrium selection in dynamic distributed systems with multiple equilibria, based on local interactions of simple memoryless agents.
Considering a fundamental game related to virus propagation on networks, we present analytical bounds on the ePoA in basic network topologies and for different strategy update dynamics. In particular, deriving stationary distributions of the stochastic evolutionary process, we find that the Nash equilibria are not always the most abundant states, and that different processes can feature significant off-equilibrium behavior, leading to a significantly higher ePoA compared to the PoA studied traditionally in the literature
Games with Delays. A Frankenstein Approach
We investigate infinite games on finite graphs where the information flow is
perturbed by nondeterministic signalling delays. It is known that such
perturbations make synthesis problems virtually unsolvable, in the general
case. On the classical model where signals are attached to states, tractable
cases are rare and difficult to identify.
Here, we propose a model where signals are detached from control states, and
we identify a subclass on which equilibrium outcomes can be preserved, even if
signals are delivered with a delay that is finitely bounded. To offset the
perturbation, our solution procedure combines responses from a collection of
virtual plays following an equilibrium strategy in the instant- signalling game
to synthesise, in a Frankenstein manner, an equivalent equilibrium strategy for
the delayed-signalling game
Evolution of Coordination in Social Networks: A Numerical Study
Coordination games are important to explain efficient and desirable social
behavior. Here we study these games by extensive numerical simulation on
networked social structures using an evolutionary approach. We show that local
network effects may promote selection of efficient equilibria in both pure and
general coordination games and may explain social polarization. These results
are put into perspective with respect to known theoretical results. The main
insight we obtain is that clustering, and especially community structure in
social networks has a positive role in promoting socially efficient outcomes.Comment: preprint submitted to IJMP
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