Chapter 5: Aggression: Stability and the Selfish Machine

Aggression: Stability and the Selfish Machine , titled Aggression: Stability and the Selfish Machine, applies game theory to evolutionary biology to explain why animals often exhibit restrained aggression rather than indiscriminate violence. Dawkins argues that treating individuals as selfish machines engaging in unconscious cost-benefit analyses provides a more rigorous explanation for animal conflict than traditional group selection theories. The central concept introduced is the Evolutionarily Stable Strategy (ESS), developed by John Maynard Smith, which is defined as a behavioral policy that, if adopted by the majority of a population, cannot be outperformed by any alternative mutant strategy. To illustrate this, the text utilizes the theoretical model of Hawks and Doves, where Hawks fight unreservedly and Doves resolve conflicts through harmless displays; mathematical analysis of the points awarded for winning, losing, wasting time, or sustaining injury reveals that neither strategy is stable on its own. Instead, a stable equilibrium evolves, often manifesting as a specific ratio of strategies within the population or a mixed probability of behaviors within individuals. The discussion expands to include more complex conditional strategies such as the Retaliator, which behaves as a Dove unless attacked, and the Prober-Retaliator, demonstrating that strategies relying on retaliation can be evolutionarily stable. The chapter also explores the War of Attrition, a contest where time is the currency of investment, concluding that the only stable strategy is to maintain a poker face, keeping the duration of one's persistence unpredictable to opponents. Furthermore, Dawkins examines asymmetric contests, where differences in size, combat ability, or arbitrary conditions like residency determine the outcome. This framework explains the logic of territorial defense, where the arbitrary convention that residents win and intruders retreat often serves as an ESS, a phenomenon supported by Niko Tinbergen’s stickleback experiments. The analysis extends to dominance hierarchies, where memory of past outcomes structures social interactions to minimize the costs of continuous fighting. Finally, the chapter broadens the ESS application to the gene pool itself, describing it as an evolutionarily stable set of genes. Using the analogy of a rowing crew, Dawkins illustrates how genes are selected not in isolation, but for their ability to function compatibly and cooperatively within the genetic environment provided by other genes in the pool.