215,582 research outputs found
Evolutionary games on multilayer networks: A colloquium
Networks form the backbone of many complex systems, ranging from the Internet
to human societies. Accordingly, not only is the range of our interactions
limited and thus best described and modeled by networks, it is also a fact that
the networks that are an integral part of such models are often interdependent
or even interconnected. Networks of networks or multilayer networks are
therefore a more apt description of social systems. This colloquium is devoted
to evolutionary games on multilayer networks, and in particular to the
evolution of cooperation as one of the main pillars of modern human societies.
We first give an overview of the most significant conceptual differences
between single-layer and multilayer networks, and we provide basic definitions
and a classification of the most commonly used terms. Subsequently, we review
fascinating and counterintuitive evolutionary outcomes that emerge due to
different types of interdependencies between otherwise independent populations.
The focus is on coupling through the utilities of players, through the flow of
information, as well as through the popularity of different strategies on
different network layers. The colloquium highlights the importance of pattern
formation and collective behavior for the promotion of cooperation under
adverse conditions, as well as the synergies between network science and
evolutionary game theory.Comment: 14 two-column pages, 8 figures; accepted for publication in European
Physical Journal
Lossy Source Transmission over the Relay Channel
Lossy transmission over a relay channel in which the relay has access to
correlated side information is considered. First, a joint source-channel
decode-and-forward scheme is proposed for general discrete memoryless sources
and channels. Then the Gaussian relay channel where the source and the side
information are jointly Gaussian is analyzed. For this Gaussian model, several
new source-channel cooperation schemes are introduced and analyzed in terms of
the squared-error distortion at the destination. A comparison of the proposed
upper bounds with the cut-set lower bound is given, and it is seen that joint
source-channel cooperation improves the reconstruction quality significantly.
Moreover, the performance of the joint code is close to the lower bound on
distortion for a wide range of source and channel parameters.Comment: Proceedings of the 2008 IEEE International Symposium on Information
Theory, Toronto, ON, Canada, July 6 - 11, 200
The Impact of CSI and Power Allocation on Relay Channel Capacity and Cooperation Strategies
Capacity gains from transmitter and receiver cooperation are compared in a
relay network where the cooperating nodes are close together. Under
quasi-static phase fading, when all nodes have equal average transmit power
along with full channel state information (CSI), it is shown that transmitter
cooperation outperforms receiver cooperation, whereas the opposite is true when
power is optimally allocated among the cooperating nodes but only CSI at the
receiver (CSIR) is available. When the nodes have equal power with CSIR only,
cooperative schemes are shown to offer no capacity improvement over
non-cooperation under the same network power constraint. When the system is
under optimal power allocation with full CSI, the decode-and-forward
transmitter cooperation rate is close to its cut-set capacity upper bound, and
outperforms compress-and-forward receiver cooperation. Under fast Rayleigh
fading in the high SNR regime, similar conclusions follow. Cooperative systems
provide resilience to fading in channel magnitudes; however, capacity becomes
more sensitive to power allocation, and the cooperating nodes need to be closer
together for the decode-and-forward scheme to be capacity-achieving. Moreover,
to realize capacity improvement, full CSI is necessary in transmitter
cooperation, while in receiver cooperation optimal power allocation is
essential.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
Punishment diminishes the benefits of network reciprocity in social dilemma experiments
Network reciprocity has been widely advertised in theoretical studies as one of the basic cooperation-promoting mechanisms, but experimental evidence favoring this type of reciprocity was published only recently. When organized in an unchanging network of social contacts, human subjects cooperate provided the following strict condition is satisfied: The benefit of cooperation must outweigh the total cost of cooperating with all neighbors. In an attempt to relax this condition, we perform social dilemma experiments wherein network reciprocity is aided with another theoretically hypothesized cooperation-promoting mechanism—costly punishment. The results reveal how networks promote and stabilize cooperation. This stabilizing effect is stronger in a smaller-size neighborhood, as expected from theory and experiments. Contrary to expectations, punishment diminishes the benefits of network reciprocity by lowering assortment, payoff per round, and award for cooperative behavior. This diminishing effect is stronger in a larger-size neighborhood. An immediate implication is that the psychological effects of enduring punishment override the rational response anticipated in quantitative models of cooperation in networks.We thank J. H. Lee for useful discussions. M.J. and Z.W. were, respectively, supported by the Research Grant Program of Inamori Foundation and the Chinese Young 1000 Talents Plan. B.P. received support from the Slovenian Research Agency (ARRS) and the Croatian Science Foundation through Projects J5-8236 and 5349, respectively. S.H. thanks the Israel-Italian collaborative project Network Cyber Security (NECST), Israel Science Foundation, Office of Naval Research (ONR), Japan Science Foundation, and the US-Israel Binational Science Foundation and the US National Science Foundation (BSF-NSF) for financial support. The Boston University Center for Polymer Studies is supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE-1213217, by Defense Threat Reduction Agency (DTRA) Grant HDTRA1-14-1-0017, and by Department of Energy (DOE) Contract DE-AC07-05Id14517. (Inamori Foundation; Chinese Young 1000 Talents Plan; J5-8236 - Slovenian Research Agency (ARRS); 5349 - Croatian Science Foundation; Israel-Italian collaborative project Network Cyber Security (NECST); Israel Science Foundation; Office of Naval Research (ONR); Japan Science Foundation; US-Israel Binational Science Foundation; US National Science Foundation (BSF-NSF); PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - Defense Threat Reduction Agency (DTRA); DE-AC07-05Id14517 - Department of Energy (DOE))Published versio
Analysis of a Cooperative Strategy for a Large Decentralized Wireless Network
This paper investigates the benefits of cooperation and proposes a relay
activation strategy for a large wireless network with multiple transmitters. In
this framework, some nodes cooperate with a nearby node that acts as a relay,
using the decode-and-forward protocol, and others use direct transmission. The
network is modeled as an independently marked Poisson point process and the
source nodes may choose their relays from the set of inactive nodes. Although
cooperation can potentially lead to significant improvements in the performance
of a communication pair, relaying causes additional interference in the
network, increasing the average noise that other nodes see. We investigate how
source nodes should balance cooperation vs. interference to obtain reliable
transmissions, and for this purpose we study and optimize a relay activation
strategy with respect to the outage probability. Surprisingly, in the high
reliability regime, the optimized strategy consists on the activation of all
the relays or none at all, depending on network parameters. We provide a simple
closed-form expression that indicates when the relays should be active, and we
introduce closed form expressions that quantify the performance gains of this
scheme with respect to a network that only uses direct transmission.Comment: Updated version. To appear in IEEE Transactions on Networkin
Evolutionary stable strategies in networked games: the influence of topology
Evolutionary game theory is used to model the evolution of competing
strategies in a population of players. Evolutionary stability of a strategy is
a dynamic equilibrium, in which any competing mutated strategy would be wiped
out from a population. If a strategy is weak evolutionarily stable, the
competing strategy may manage to survive within the network. Understanding the
network-related factors that affect the evolutionary stability of a strategy
would be critical in making accurate predictions about the behaviour of a
strategy in a real-world strategic decision making environment. In this work,
we evaluate the effect of network topology on the evolutionary stability of a
strategy. We focus on two well-known strategies known as the Zero-determinant
strategy and the Pavlov strategy. Zero-determinant strategies have been shown
to be evolutionarily unstable in a well-mixed population of players. We
identify that the Zero-determinant strategy may survive, and may even dominate
in a population of players connected through a non-homogeneous network. We
introduce the concept of `topological stability' to denote this phenomenon. We
argue that not only the network topology, but also the evolutionary process
applied and the initial distribution of strategies are critical in determining
the evolutionary stability of strategies. Further, we observe that topological
stability could affect other well-known strategies as well, such as the general
cooperator strategy and the cooperator strategy. Our observations suggest that
the variation of evolutionary stability due to topological stability of
strategies may be more prevalent in the social context of strategic evolution,
in comparison to the biological context
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