1,801 research outputs found
Distributed Learning Policies for Power Allocation in Multiple Access Channels
We analyze the problem of distributed power allocation for orthogonal
multiple access channels by considering a continuous non-cooperative game whose
strategy space represents the users' distribution of transmission power over
the network's channels. When the channels are static, we find that this game
admits an exact potential function and this allows us to show that it has a
unique equilibrium almost surely. Furthermore, using the game's potential
property, we derive a modified version of the replicator dynamics of
evolutionary game theory which applies to this continuous game, and we show
that if the network's users employ a distributed learning scheme based on these
dynamics, then they converge to equilibrium exponentially quickly. On the other
hand, a major challenge occurs if the channels do not remain static but
fluctuate stochastically over time, following a stationary ergodic process. In
that case, the associated ergodic game still admits a unique equilibrium, but
the learning analysis becomes much more complicated because the replicator
dynamics are no longer deterministic. Nonetheless, by employing results from
the theory of stochastic approximation, we show that users still converge to
the game's unique equilibrium.
Our analysis hinges on a game-theoretical result which is of independent
interest: in finite player games which admit a (possibly nonlinear) convex
potential function, the replicator dynamics (suitably modified to account for
nonlinear payoffs) converge to an eps-neighborhood of an equilibrium at time of
order O(log(1/eps)).Comment: 11 pages, 8 figures. Revised manuscript structure and added more
material and figures for the case of stochastically fluctuating channels.
This version will appear in the IEEE Journal on Selected Areas in
Communication, Special Issue on Game Theory in Wireless Communication
Statistical mechanics and stability of a model eco-system
We study a model ecosystem by means of dynamical techniques from disordered
systems theory. The model describes a set of species subject to competitive
interactions through a background of resources, which they feed upon.
Additionally direct competitive or co-operative interaction between species may
occur through a random coupling matrix. We compute the order parameters of the
system in a fixed point regime, and identify the onset of instability and
compute the phase diagram. We focus on the effects of variability of resources,
direct interaction between species, co-operation pressure and dilution on the
stability and the diversity of the ecosystem. It is shown that resources can be
exploited optimally only in absence of co-operation pressure or direct
interaction between species.Comment: 23 pages, 13 figures; text of paper modified, discussion extended,
references adde
The prisoners dilemma on a stochastic non-growth network evolution model
We investigate the evolution of cooperation on a non - growth network model
with death/birth dynamics. Nodes reproduce under selection for higher payoffs
in a prisoners dilemma game played between network neighbours. The mean field
characteristics of the model are explored and an attempt is made to understand
the size dependent behaviour of the model in terms of fluctuations in the
strategy densities. We also briefly comment on the role of strategy mutation in
regulating the strategy densties.Comment: 8 pages, 8 figure
Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics
Evolutionary game dynamics is one of the most fruitful frameworks for
studying evolution in different disciplines, from Biology to Economics. Within
this context, the approach of choice for many researchers is the so-called
replicator equation, that describes mathematically the idea that those
individuals performing better have more offspring and thus their frequency in
the population grows. While very many interesting results have been obtained
with this equation in the three decades elapsed since it was first proposed, it
is important to realize the limits of its applicability. One particularly
relevant issue in this respect is that of non-mean-field effects, that may
arise from temporal fluctuations or from spatial correlations, both neglected
in the replicator equation. This review discusses these temporal and spatial
effects focusing on the non-trivial modifications they induce when compared to
the outcome of replicator dynamics. Alongside this question, the hypothesis of
linearity and its relation to the choice of the rule for strategy update is
also analyzed. The discussion is presented in terms of the emergence of
cooperation, as one of the current key problems in Biology and in other
disciplines.Comment: Review, 48 pages, 26 figure
The Impact of Network Flows on Community Formation in Models of Opinion Dynamics
We study dynamics of opinion formation in a network of coupled agents. As the
network evolves to a steady state, opinions of agents within the same community
converge faster than those of other agents. This framework allows us to study
how network topology and network flow, which mediates the transfer of opinions
between agents, both affect the formation of communities. In traditional models
of opinion dynamics, agents are coupled via conservative flows, which result in
one-to-one opinion transfer. However, social interactions are often
non-conservative, resulting in one-to-many transfer of opinions. We study
opinion formation in networks using one-to-one and one-to-many interactions and
show that they lead to different community structure within the same network.Comment: accepted for publication in The Journal of Mathematical Sociology.
arXiv admin note: text overlap with arXiv:1201.238
Social Network Reciprocity as a Phase Transition in Evolutionary Cooperation
In Evolutionary Dynamics the understanding of cooperative phenomena in
natural and social systems has been the subject of intense research during
decades. We focus attention here on the so-called "Lattice Reciprocity"
mechanisms that enhance evolutionary survival of the cooperative phenotype in
the Prisoner's Dilemma game when the population of darwinian replicators
interact through a fixed network of social contacts. Exact results on a "Dipole
Model" are presented, along with a mean-field analysis as well as results from
extensive numerical Monte Carlo simulations. The theoretical framework used is
that of standard Statistical Mechanics of macroscopic systems, but with no
energy considerations. We illustrate the power of this perspective on social
modeling, by consistently interpreting the onset of lattice reciprocity as a
thermodynamical phase transition that, moreover, cannot be captured by a purely
mean-field approach.Comment: 10 pages. APS styl
- …