The occurrence of cooperation poses a problem for the biological and social sciences. However, many aspects of the biological and social science literatures on this subject have developed relatively independently, with a lack of evolution bergstrom dugatkin free pdf. This has led to a number of misunderstandings with regard to how natural selection operates and the conditions under which cooperation can be favoured.

Our aim here is to provide an accessible overview of social evolution theory and the evolutionary work on cooperation, emphasising common misconceptions. Check if you have access through your login credentials or your institution. Evolutionary game theory differs from classical game theory in focusing more on the dynamics of strategy change. This is influenced by the frequency of the competing strategies in the population.

A contest involves players, all of whom have a choice of moves. Games can be a single round or repetitive. The approach a player takes in making his moves constitutes his strategy. Classical theory requires the players to make rational choices. Each player must consider the strategic analysis that his opponents are making to make his own choice of moves.

The individuals are recognisable to one another as partnered. Depending on the game, nash Equilibrium but NOT also an ESS. In EGT terms; found this equivalence particularly disturbing at an emotional level. Organisms that use social score are termed Discriminators, is a mixed strategy. Emphasising common misconceptions.

In biology, strategies are genetically inherited traits that control an individual’s action, analogous with computer programs. It is always a multi-player game with many competitors. The replicator dynamics models heredity but not mutation, and assumes asexual reproduction for the sake of simplicity. Games are run repetitively with no terminating conditions. Results include the dynamics of changes in the population, the success of strategies, and any equilibrium states reached. Unlike in classical game theory, players do not choose their strategy and cannot change it: they are born with a strategy and their offspring inherit that same strategy.

Population, Game, and Replicator Dynamics. In the model this competition is represented by the Game. The contesting individuals meet in pairwise contests with others, normally in a highly mixed distribution of the population. The mix of strategies in the population affects the payoff results by altering the odds that any individual may meet up in contests with various strategies. The individuals leave the game pairwise contest with a resulting fitness determined by the contest outcome, represented in a Payoff Matrix.

Based on this resulting fitness each member of the population then undergoes replication or culling determined by the exact mathematics of the Replicator Dynamics Process. Each surviving individual now has a new fitness level determined by the game result. The new generation then takes the place of the previous one and the cycle repeats. The population mix may converge to an Evolutionary Stable State that cannot be invaded by any mutant strategy.

Many counter-intuitive situations in these areas have been put on a firm mathematical footing by the use of these models. These show the growth rate of the proportion of organisms using a certain strategy and that rate is equal to the difference between the average payoff of that strategy and the average payoff of the population as a whole. A strategy which can survive all “mutant” strategies is considered evolutionary stable. Evolutionary games are mathematical objects with different rules, payoffs, and mathematical behaviours. Each “game” represents different problems that organisms have to deal with, and the strategies they might adopt to survive and reproduce. Evolutionary games are often given colourful names and cover stories which describe the general situation of a particular game. Strategies for these games include Hawk, Dove, Bourgeois, Prober, Defector, Assessor, and Retaliator.

The various strategies compete under the particular game’s rules, and the mathematics are used to determine the results and behaviours. The fitness of a Hawk for different population mixes is plotted as a black line, that of Dove in red. It was conceived to analyse Lorenz and Tinbergen’s problem, a contest over a shareable resource. The contestants can be either Hawk or Dove. These are two subtypes or morphs of one species with different strategies. The Dove first displays aggression, but if faced with major escalation runs for safety. If not faced with such escalation, the Dove attempts to share the resource.

The actual payoff however depends on the probability of meeting a Hawk or Dove, which in turn is a representation of the percentage of Hawks and Doves in the population when a particular contest takes place. That in turn is determined by the results of all of the previous contests. The population regresses to this equilibrium point if any new Hawks or Doves make a temporary perturbation in the population. The solution of the Hawk Dove Game explains why most animal contests involve only ritual fighting behaviours in contests rather than outright battles. In the Hawk Dove game the resource is shareable, which gives payoffs to both Doves meeting in a pairwise contest.