3,092 research outputs found
Evolutionary games on graphs
Game theory is one of the key paradigms behind many scientific disciplines
from biology to behavioral sciences to economics. In its evolutionary form and
especially when the interacting agents are linked in a specific social network
the underlying solution concepts and methods are very similar to those applied
in non-equilibrium statistical physics. This review gives a tutorial-type
overview of the field for physicists. The first three sections introduce the
necessary background in classical and evolutionary game theory from the basic
definitions to the most important results. The fourth section surveys the
topological complications implied by non-mean-field-type social network
structures in general. The last three sections discuss in detail the dynamic
behavior of three prominent classes of models: the Prisoner's Dilemma, the
Rock-Scissors-Paper game, and Competing Associations. The major theme of the
review is in what sense and how the graph structure of interactions can modify
and enrich the picture of long term behavioral patterns emerging in
evolutionary games.Comment: Review, final version, 133 pages, 65 figure
Range expansion with mutation and selection: dynamical phase transition in a two-species Eden model
The colonization of unoccupied territory by invading species, known as range expansion, is a spatially heterogeneous non-equilibrium growth process. We introduce a two-species Eden growth model to analyze the interplay between uni-directional (irreversible) mutations and selection at the expanding front. While the evolutionary dynamics leads to coalescence of both wild-type and mutant clusters, the non-homogeneous advance of the colony results in a rough front. We show that roughening and domain dynamics are strongly coupled, resulting in qualitatively altered bulk and front properties. For beneficial mutations the front is quickly taken over by mutants and growth proceeds Eden-like. In contrast, if mutants grow slower than wild-types, there is an antagonism between selection pressure against mutants and growth by the merging of mutant domains with an ensuing absorbing state phase transition to an all-mutant front. We find that surface roughening has a marked effect on the critical properties of the absorbing state phase transition. While reference models, which keep the expanding front flat, exhibit directed percolation critical behavior, the exponents of the two-species Eden model strongly deviate from it. In turn, the mutation-selection process induces an increased surface roughness with exponents distinct from that of the classical Eden model
The pace of evolution across fitness valleys
How fast does a population evolve from one fitness peak to another? We study
the dynamics of evolving, asexually reproducing populations in which a certain
number of mutations jointly confer a fitness advantage. We consider the time
until a population has evolved from one fitness peak to another one with a
higher fitness. The order of mutations can either be fixed or random. If the
order of mutations is fixed, then the population follows a metaphorical ridge,
a single path. If the order of mutations is arbitrary, then there are many ways
to evolve to the higher fitness state. We address the time required for
fixation in such scenarios and study how it is affected by the order of
mutations, the population size, the fitness values and the mutation rate
Phase transition in a spatial Lotka-Volterra model
Spatial evolution is investigated in a simulated system of nine competing and
mutating bacterium strains, which mimics the biochemical war among bacteria
capable of producing two different bacteriocins (toxins) at most. Random
sequential dynamics on a square lattice is governed by very symmetrical
transition rules for neighborhood invasion of sensitive strains by killers,
killers by resistants, and resistants by by sensitives. The community of the
nine possible toxicity/resistance types undergoes a critical phase transition
as the uniform transmutation rates between the types decreases below a critical
value above which all the nine types of strain coexist with equal
frequencies. Passing the critical mutation rate from above, the system
collapses into one of the three topologically identical states, each consisting
of three strain types. Of the three final states each accrues with equal
probability and all three maintain themselves in a self-organizing polydomain
structure via cyclic invasions. Our Monte Carlo simulations support that this
symmetry breaking transition belongs to the universality class of the
three-state Potts model.Comment: 4 page
Evolution of new regulatory functions on biophysically realistic fitness landscapes
Regulatory networks consist of interacting molecules with a high degree of
mutual chemical specificity. How can these molecules evolve when their function
depends on maintenance of interactions with cognate partners and simultaneous
avoidance of deleterious "crosstalk" with non-cognate molecules? Although
physical models of molecular interactions provide a framework in which
co-evolution of network components can be analyzed, most theoretical studies
have focused on the evolution of individual alleles, neglecting the network. In
contrast, we study the elementary step in the evolution of gene regulatory
networks: duplication of a transcription factor followed by selection for TFs
to specialize their inputs as well as the regulation of their downstream genes.
We show how to coarse grain the complete, biophysically realistic
genotype-phenotype map for this process into macroscopic functional outcomes
and quantify the probability of attaining each. We determine which evolutionary
and biophysical parameters bias evolutionary trajectories towards fast
emergence of new functions and show that this can be greatly facilitated by the
availability of "promiscuity-promoting" mutations that affect TF specificity
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