6 research outputs found
Evolutionary Games on Networks and Payoff Invariance Under Replicator Dynamics
The commonly used accumulated payoff scheme is not invariant with respect to
shifts of payoff values when applied locally in degree-inhomogeneous population
structures. We propose a suitably modified payoff scheme and we show both
formally and by numerical simulation, that it leaves the replicator dynamics
invariant with respect to affine transformations of the game payoff matrix. We
then show empirically that, using the modified payoff scheme, an interesting
amount of cooperation can be reached in three paradigmatic non-cooperative
two-person games in populations that are structured according to graphs that
have a marked degree inhomogeneity, similar to actual graphs found in society.
The three games are the Prisoner's Dilemma, the Hawks-Doves and the Stag-Hunt.
This confirms previous important observations that, under certain conditions,
cooperation may emerge in such network-structured populations, even though
standard replicator dynamics for mixing populations prescribes equilibria in
which cooperation is totally absent in the Prisoner's Dilemma, and it is less
widespread in the other two games.Comment: 20 pages, 8 figures; to appear on BioSystem
Mutual Trust and Cooperation in the Evolutionary Hawks-Doves Game
Using a new dynamical network model of society in which pairwise interactions
are weighted according to mutual satisfaction, we show that cooperation is the
norm in the Hawks-Doves game when individuals are allowed to break ties with
undesirable neighbors and to make new acquaintances in their extended
neighborhood. Moreover, cooperation is robust with respect to rather strong
strategy perturbations. We also discuss the empirical structure of the emerging
networks, and the reasons that allow cooperators to thrive in the population.
Given the metaphorical importance of this game for social interaction, this is
an encouraging positive result as standard theory for large mixing populations
prescribes that a certain fraction of defectors must always exist at
equilibrium.Comment: 23 pages 12 images, to appea
Coevolutionary games - a mini review
Prevalence of cooperation within groups of selfish individuals is puzzling in
that it contradicts with the basic premise of natural selection. Favoring
players with higher fitness, the latter is key for understanding the challenges
faced by cooperators when competing with defectors. Evolutionary game theory
provides a competent theoretical framework for addressing the subtleties of
cooperation in such situations, which are known as social dilemmas. Recent
advances point towards the fact that the evolution of strategies alone may be
insufficient to fully exploit the benefits offered by cooperative behavior.
Indeed, while spatial structure and heterogeneity, for example, have been
recognized as potent promoters of cooperation, coevolutionary rules can extend
the potentials of such entities further, and even more importantly, lead to the
understanding of their emergence. The introduction of coevolutionary rules to
evolutionary games implies, that besides the evolution of strategies, another
property may simultaneously be subject to evolution as well. Coevolutionary
rules may affect the interaction network, the reproduction capability of
players, their reputation, mobility or age. Here we review recent works on
evolutionary games incorporating coevolutionary rules, as well as give a
didactic description of potential pitfalls and misconceptions associated with
the subject. In addition, we briefly outline directions for future research
that we feel are promising, thereby particularly focusing on dynamical effects
of coevolutionary rules on the evolution of cooperation, which are still widely
open to research and thus hold promise of exciting new discoveries.Comment: 24 two-column pages, 10 figures; accepted for publication in
BioSystem
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
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Coevolution of risk aversion, trust and trustworthiness: an agent-based approach
The research presented here deals with the evolution of personality features of humans engaged in strategic interactions. The evolution of risk aversion and trustworthiness is modelled and simulated in the context of a binary trust game, seeking the origin and end-points of an evolutionary process, accounting for different degrees of locality.
This research has employed computer simulations in order to get dynamic equilibria in populations of players that keep evolving. The locality or global nature of interaction plays an important role. Risk aversion evolves together with trust and trustworthiness. Trust behaviour follows reciprocation attributes. Results of the simulations are equal to the ones elicited in empirical studies