Tit-for-Tat Approach to Survival: Evolutionary Strategies
In biology, an evolutionarily stable strategy describes the set of behaviors for a population where, if the strategy is adopted by every individual, it would be highly difficult for outsiders to penetrate the group with any alternative strategies. Groups of animals, or populations, may naturally build up certain strategies for their collective benefit, adopting an evolutionarily stable strategy, that is not effective in the short term, but in the long term. In the example we will discuss below, the competition for survival can be reduced down to the iterated prisoner’s dilemma (IPD), which aims to answer them problem of what the optimal strategy would be when the individuals involved in the game has to devise a new strategy, game after game. Through a programming tournament where participants were instructed to create an algorithm to find the solution to the dilemma – an optimal strategy – it was discovered that the “tit-for-tat” approach would be the most effective.
The approach is reciprocal: an individual would first choose to cooperate with their opponent, and in subsequent rounds, would mirror the decisions of the opponent. Some principles of the approach include being “nice,” “retaliating,” and “forgiving.” By being altruistic when the opponent is, and not when the opponent isn’t, and willing to cooperate in the future if the opponent shows willingness to be altruistic, both participants of the game are able to reap the benefits of collaboration.
For example, when an outsider attempts to attack a community of animals, a member can choose to either make noise to alert others, or to stay silent and protect themselves only. In a single game, the prisoner’s dilemma applies. Rationally, the individual will benefit by staying quiet, and not drawing the attention of the predator. However, the individual, in the long-term, will benefit by alerting others and have them alert themselves too when danger approaches. Such collaboration motivates the individual that first notices danger to risk their lives, and act in the community’s best interest. This example shows how game theory can be applied to communities of living organisms, and how the responses of participants can change depending on whether or not they are aware of the “total” number of games that will be played in the future.
https://www.quantamagazine.org/game-theory-explains-how-cooperation-evolved-20150212/
https://lawrules.wordpress.com/2011/09/05/the-axelrod-tournaments/