Sharp Benefit-to-Cost Rules for the Evolution of Cooperation on Regular Graphs

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We study two of the simple rules on finite graphs under the death-birth updating and the imitation updating discovered by Ohtsuki, Hauert, Lieberman, and Nowak [\emph{Nature} {\bf 441} (2006) 502-505]. Each rule specifies a payoff-ratio cutoff point for the magnitude of fixation probabilities of the underlying evolutionary game between cooperators and defectors. We view the Markov chains associated with the two updating mechanisms as voter model perturbations. Then we present a first-order approximation for fixation probabilities of general voter model perturbations on finite graphs subject to small perturbation in terms of the voter model fixation probabilities. In the context of regular graphs, we obtain algebraically explicit first-order approximations for the fixation probabilities of cooperators distributed as certain uniform distributions. These approximations lead to a rigorous proof that both of the rules of Ohtsuki et al. are valid and are sharp.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Sharp Benefit-to-Cost Rules for the Evolution of Cooperation on Regular Graphs does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Sharp Benefit-to-Cost Rules for the Evolution of Cooperation on Regular Graphs, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Sharp Benefit-to-Cost Rules for the Evolution of Cooperation on Regular Graphs will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-221603

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.