2,237 research outputs found
Evolving quorum sensing in digital organisms
For centuries it was thought that bacteria live asocial lives. However, recent discoveries show many species of bacteria communicate in order to perform tasks previously thought to be limited to multicellular organisms. Central to this capability is quorum sensing, whereby organisms detect cell density and use this information to trigger group behaviors. Quorum sensing is used by bacteria in the formation of biofilms, secretion of digestive enzymes and, in the case of pathogenic bacteria, release of toxins or other virulence factors. Indeed, methods to disrupt quorum sensing are currently being investigated as possible treatments for numerous diseases, including cystic fibrosis, epidemic cholera, and methicillin-resistant Staphylococcus aureus. In this paper we demonstrate the evolution of a quorum sensing behavior in populations of digital organisms. Specifically, we show that digital organisms are capable of evolving a strategy to collectively suppress self-replication, when the population density reaches a specific, evolved threshold. We present the evolved genome of an organism exhibiting this behavior and analyze the collective operation of this “algorithm. ” Finally, through a set of experiments we demonstrate that the behavior scales to populations up to 400 times larger than those in which the behavior evolved
More Bang For Your Buck: Quorum-Sensing Capabilities Improve the Efficacy of Suicidal Altruism
Within the context of evolution, an altruistic act that benefits the
receiving individual at the expense of the acting individual is a puzzling
phenomenon. An extreme form of altruism can be found in colicinogenic E. coli.
These suicidal altruists explode, releasing colicins that kill unrelated
individuals, which are not colicin resistant. By committing suicide, the
altruist makes it more likely that its kin will have less competition. The
benefits of this strategy rely on the number of competitors and kin nearby. If
the organism explodes at an inopportune time, the suicidal act may not harm any
competitors. Communication could enable organisms to act altruistically when
environmental conditions suggest that that strategy would be most beneficial.
Quorum sensing is a form of communication in which bacteria produce a protein
and gauge the amount of that protein around them. Quorum sensing is one means
by which bacteria sense the biotic factors around them and determine when to
produce products, such as antibiotics, that influence competition. Suicidal
altruists could use quorum sensing to determine when exploding is most
beneficial, but it is challenging to study the selective forces at work in
microbes. To address these challenges, we use digital evolution (a form of
experimental evolution that uses self-replicating computer programs as
organisms) to investigate the effects of enabling altruistic organisms to
communicate via quorum sensing. We found that quorum-sensing altruists killed a
greater number of competitors per explosion, winning competitions against
non-communicative altruists. These findings indicate that quorum sensing could
increase the beneficial effect of altruism and the suite of conditions under
which it will evolve.Comment: 8 pages, 8 figures, ALIFE '14 conferenc
Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures
We investigate fundamental decisions in the design of instruction set
architectures for linear genetic programs that are used as both model systems
in evolutionary biology and underlying solution representations in evolutionary
computation. We subjected digital organisms with each tested architecture to
seven different computational environments designed to present a range of
evolutionary challenges. Our goal was to engineer a general purpose
architecture that would be effective under a broad range of evolutionary
conditions. We evaluated six different types of architectural features for the
virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more
precisely modify the function of genetic instructions, (2) memory: we provided
an increased number of registers in the virtual CPUs, (3) decoupled sensors and
actuators: we separated input and output operations to enable greater control
over data flow. We also tested a variety of methods to regulate expression: (4)
explicit labels that allow programs to dynamically refer to specific genome
positions, (5) position-relative search instructions, and (6) multiple new flow
control instructions, including conditionals and jumps. Each of these features
also adds complication to the instruction set and risks slowing evolution due
to epistatic interactions. Two features (multiple argument specification and
separated I/O) demonstrated substantial improvements int the majority of test
environments. Some of the remaining tested modifications were detrimental,
thought most exhibit no systematic effects on evolutionary potential,
highlighting the robustness of digital evolution. Combined, these observations
enhance our understanding of how instruction architecture impacts evolutionary
potential, enabling the creation of architectures that support more rapid
evolution of complex solutions to a broad range of challenges
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