Evolutionary Stable Strategy

views updated May 21 2018

Evolutionary Stable Strategy

An evolutionary stable strategy describes tactics employed by individual organisms when competing with one another for a given resource. These tactics can be behavioral or structural, and the organism does not consciously choose them, but adopts them as a natural consequence of evolution. Both structures and behaviors are heritable (capable of being inherited), and as some are successful and some fail, only the better ones are passed on. It is important to differentiate between a strategy employed by an individual, such as displaying brighter-colored feathers, and a strategic decision an individual might consciously make, such as going to medical school, because only heritable strategies get passed on to offspring. Decisions such as going to medical school, however strong in a family, are not heritable.

The idea of evolutionary stable strategy (ESS) was first conceived by the British biologist John Maynard Smith in 1974. The idea is that one strategy in a given contest, on average, will win over any other strategy. The strategy should also have the benefit of doing well when pitted against opponents employing the same strategy. This is important, because a successful strategy is likely to be common and an organism will probably have to compete with others who are employing it. There does not necessarily have to be a single evolutionary strategy. It can be a combination of strategies, or a combination of individuals who each employ only one strategy.

The workings of an evolutionary stable strategy can be illustrated by looking at a simple system of two strategies. Suppose a given population of organisms has to compete for food. In this particular population, there only two possible strategies. Individuals can act like "hawks," which will fight over a piece of food viciously and retreat only when seriously injured, or they can act like "doves," which will try to puff their chests out and pretend to be tough, but run away at the threat of any serious challenge. Hawks will always beat doves. When hawks fight hawks, there will be a winner and a loser, but the loser will be seriously injured. Doves fighting doves will display at one another for a period of time before giving up. Neither will be injured, but they will have wasted some of the time they could have spent looking for food.

Opponent
HawkDove
PlayerHawk50 or-100, average-25Always 50
DoveAlways 040 or-10, average 15

Which is the better strategy? That is, is it better to be a hawk and win against all doves, but at the risk of serious injury, or is it better to be a dove and risk being trounced by hawks? To answer this question, the British evolutionary biologist Richard Dawkins assigned arbitrary scores to wins and losses. He awarded 50 points for a win, zero points for losing, minus 100 points for serious injury, and minus 10 points for wasting time with excessive displays. Under Dawkins's system, assuming a record of equal wins and losses for evenly matched competitors, a bird population consisting exclusively of doves would reward individuals with an average of 15 points per contest. If a dove wins a contest against a dove, he gets 50 points less 10 points for wasting time, for a total of 40 points. The loser gets minus 10. If an individual wins half his contests, his score averages to 15 points (40 points minus 10 points divided by 2).

However, we cannot assume that a population of only doves would be evolutionarily stable. Although such a population seems beneficial for all the individuals involved, what happens if a mutation takes place, or a sudden immagrant flies in, and a hawk appears in the population? The hawk will win all his contests, and reproduce quickly and often. Before long, the successful hawks could possibly drive the doves into extinction. However, at a price of minus 100 points per loss, a hawk surrounded exclusively by hawks will average minus 25 points, whereas a dove surrounded by hawks will score zero. So in a population of only hawks, doves will tend to do better. A population of only hawks would not be evolutionarily stable, either. Over time, a single strategy cannot sustain itself.

So what strategy is evolutionarily stable? In this particular population, the stable strategy is a mixture of doves and hawks. This could mean that individuals never change their strategies and that a combination of both strategies is stable, or that individuals may employ either strategy and switch strategies as often as they please. In this case, the average individual will employ the most advantageous proportions of either strategy. In a system with 12 individuals5 doves and 7 hawksthe average payoff for any individual is 6.25. Thus, we could have 5 individuals that were always doves and 7 that were always hawks, or 12 individuals that were doves 5/12 of the time and hawks the rest.

Of course, this is a very simple system. If individuals switch strategies, it is assumed that the organism's opponents are unable to guess its intentions. If the organism could not disguise its intentions, enemies could quickly learn to detect outward signs of strategy choice and adjust their tactics accordingly. For example, if an individual scratched at the sand every time before deciding to be a dove, its opponents could learn to be a hawk every time sand was scratched, and they would always win.

In nature, of course, different strategies are tried all the time. Instead of just two, there is a nearly infinite number of potential tactics, and it is reasonable to imagine that mutations are happening at a constant rate that introduces new tactics, or reintroduces old ones, into the system. These new strategies may topple the old ESS, or they may not. A preexisting ESS has probably been challenged by any number of alternate strategies and has survived, but it might be expected that only a completely new and innovative strategy would have a fighting chance at defeating it.

In 1980, the American political scientist Robert Axelrod created a contest related to the hawks-vs.-doves scenario, but allowed fifteen different strategies to compete in a computer simulation. After hundreds of rounds, a consistent winner cropped up, which may be safely called the evolutionary stable strategy. Fifteen opponents with a variety of tactics could not defeat it. Axelrod held another contest, this one with sixty-three entrants, and came up with the same winning strategy.

Such contests happen constantly in nature. New strategies evolve and pit themselves against the present evolutionary stable strategy. Given the diversity of the opponents that show up, the strategy is tested in a variety of directions. A true ESS will be unshakeable regardless of the opponents. Of course, in nature, changes in an organism's physical environment or species invasion can change all the rules of the game, and strategies may topple and be replaced by others better suited to the new environment.

Ian Quigley

Bibliography

Dawkins, Richard. The Selfish Gene. New York: Oxford University Press, 1989.

evolutionary stable strategy

views updated Jun 27 2018

evolutionary stable strategy (ESS) In the application of game theory to evolutionary studies, moves in the game that cannot be beaten; i.e. traits or combinations of traits cannot be replaced by any invading mutant. Evolutionary stable strategy theory has proved very useful in the analysis of certain types of animal behaviour.

evolutionary stable strategy

views updated May 29 2018

evolutionary stable strategy (ESS) In the application of game theory to evolutionary studies, moves in the game that cannot be beaten; i.e. traits or combinations of traits cannot be replaced by any invading mutant. Evolutionary stable strategy theory has proved very useful in the analysis of certain types of animal behaviour.