 As we saw in the previous video on evolutionary games, when everyone was playing a random strategy, it was best to play a tit for tat strategy. When everyone was playing a tit for tat strategy, it was best to play generous tit for tat. When people were playing this, it was then best to play an unconditionally cooperative strategy. Once the game was in this state, it was then best to play a defecting strategy and thus creating a cycle. This illustrates clearly the dynamic nature to the success of strategies within games. Because evolutionary games are dynamic, meaning that agent strategies change over time. What is best for one agent to do often depends on what others are doing. It is then legitimate for us to ask, are there any strategies within a given game that are stable and resistant to invasion? In studying evolutionary games, one thing that biologists and others have been particularly interested in is the idea of evolutionary stability, which are evolutionary games that lead to stable solutions or points of stasis for the contending strategies. Just as equilibrium is the central idea within static non-corporative games, the central idea in dynamic games is that of evolutionary stable strategies, as those that will endure over time. As an example, we can think about a population of seals that goes out fishing every day. Hunting for fish is energy consuming and thus some seals may adopt a strategy of simply stealing the fish off those who have gone out fishing. So when a whole population is fishing, then if an individual mutant might be born that follows a defect strategy of stealing, it would then do well for itself because there is plenty of fishing happening. This successful defect strategy would then reproduce creating more defectors, at which point we might say that this defecting strategy is superior and will dominate others. But of course over time, we will get a tragedy of the common situation emerge as not enough seals are going out fishing. Stealing fish will become a less viable strategy to the point where they die out all together and those who are going fishing may do well for themselves again. Thus the defector strategy can be said to be evolutionally unstable and likewise the fishing strategy may also be unstable. What may be stable in this evolutionary game is some combination of both. The evolutionary stable strategy concept is very much similar to the Nash Equilibrium within classical game theory with a number of additions. Nash Equilibrium is a game equilibrium where it is not rational for any player to deviate from their present strategy. An evolutionary stable strategy is a state of game dynamics where in a very large population of competitors another mutant strategy cannot successfully enter the population to disturb the existing dynamic. Indeed in the modern view equilibrium should be thought of as the limiting outcome of an unspecified learning or evolutionary process that unfolds over time. In this view equilibrium is the end story of how strategic thinking, competition, optimization and learning work not the beginning or middle of a one-shot game. Therefore a successful stable strategy must have at least two characteristics. Firstly it must be effective against competitors when it is still rare so that it can enter the previous competing population and grow. Secondly it must also be successful later when it has grown to a high proportion of the population so that it can defend itself against future mutants. This in turn means that the strategy must be successful when it contends with others exactly like itself. A stable strategy in an evolutionary game does not have to be unbeatable, it only has to be uninvatable and thus stable over time. A stable strategy is a strategy that when everyone is doing it no new mutants could arise which would do better and from that we could expect a degree of stability. Of course we don't always get stable strategies emerge within evolutionary games. One of the simplest examples of this is the game Rock Paper Scissors. The best strategy is to play a mixed random game where one plays any of the three strategies one third of the time. However in biology many creatures are incapable of mixed behavior, they only exhibit one pure strategy. If the game is played only with pure rock paper and scissors strategies the evolutionary game is dynamically unstable. Rock mutants can enter an all scissors population but then paper mutants can take over an all rock population but then again scissor mutants can take over an all paper population and so on. Using experimental economic methods scientists have used the rock paper scissors game to test human social evolutionary dynamic behaviors in the laboratory. The social cyclical behaviors predicted by evolutionary game theory have been observed in various lab experiments. Likewise it has been recorded within ecosystems most notably within a particular type of lizard that can have three different forms creating three different strategies. One of being aggressive, the other unaggressive and the third somewhat prudent. The overall situation corresponds to the rock scissors paper game creating a six year population cycle as new mutants enter and become dominant before another strategy invades and so on.