SELFISH GENE THEORY AND GAME THEORY
Understanding selfish gene theory requires understanding how game theory, specifically the Nash equilibrium of mutual-best-reply, is proposed to be the deductive model explaining the mechanism by which evolution functions.[615] This section discusses the basic model of game theoretic evolution, which is projected back onto anecdotal studies of particular niches of animal behavior.
To apply game theory, a unit of action performing optimization must be identified. This of course is Dawkins’s gene. This unitary actor is a parcel characterized by a complete set of strategies defining action choices in all conceivable circumstances.[616] Strategies are rules for action. Dawkins explains, “Animals have to be given by their genes a simple rule for action, a rule that does not involve all-wise cognition of the ultimate purpose of the action, but a rule that works nevertheless, at least in average conditions.”[617] In essence, Dawkins’s gene is a unit of action that has a strategy set determining what to do in the normal circumstances it routinely encounters. Successful action is that defined as the continuation and replication of existence such that the genetic material a gene is programmed into is represented in the next generation of actors. Dawkins elucidates,Every decision that a survival machine takes is a gamble, and it is the business of genes to program brains in advance so that on average they take decisions that pay off. The currency used in the casino of evolution is survival, strictly gene survival, but for many purposes individual survival is a reasonable approximation.[618]
Game theory introduces a reward structure for decision outcomes reflecting fitness value. The same rules for survival apply at the genetic and individual levels.
Dawkins applies his metaphor that is apt for neoliberal capitalism directly to units of DNA demarcated as genes. Within the evolutionary context, actors’, in this case genes’, preference rankings are externally supplied by the objective conditions characterizing the environment.Selfish gene theory identifies the gene as the basic unit containing a strategy set determining action choices. The central idea is that the gene acts as if its fundamental mission were to procreate. Therefore, it as as though it aims to maximize an objective function directly correlating to its survival chances. Even though it may appear that the actor actively intends to survive, this view introduces an unwelcome teleology. Rather, it is appropriate to see that the genetic agents that did successfully survive and procreate had to have made choices that maximized their survival chances.[619] The application of noncooperative game theory to the gene, instead of to a group, introduces the assumption of methodological individualism. Noncooperative game theory vindicates selfish gene theory because it stipulates that elementary unitary actors optimize a function against one another; it does not permit joint maximization.[620] Noncooperative game theory is consistent with the widely accepted assumption that natural selection does not occur at the level of groups.[621] Individuals are responsible for their own survival chances in accordance with each individual’s achieved fitness level and with more favorable odds that types of individuals with superior survival strategies encounter. This visualization of the mechanism of natural selection suggests that each individual actor must be viable in every round of engagement, much as how in neoliberal economic systems, all individuals are responsible for their self-care on a pay-as-you-go basis.
Once Dawkins has introduced the concept of the gene as a primary unit of action best thought of as a strategy set programming an organism’s behavior so that it must act as though it is maximizing an objective function to exist, he quickly moves into the territory of game theory.
He uses John Nash’s equilibrium concept to argue that populations of individual members must live in this kind of equilibrium characterized by stable repeating patterns of mutual-best- replies.[622] Prior to evolutionary game theory, game theorists emphasized onetime games or games repeated over a fixed number of plays. In John von Neumann and Oskar Morgenstern’s original two-person zero-sum games, indefinitely repeating games were contemplated as a mathematical artifice that rationalized mixed strategies, meaning those incorporating choice based on die rolls. However, within the context of evolution, theorists considered games played repeatedly over thousands or even millions of years. From this perspective, Nash’s equilibrium concept of mutual-best-reply could be considered the outcome of a dynamic process in which agents compete with each other for objective value, and their phenotype is represented in the next generation according to their success relative to other phenotypes. In equilibrium, it does not behoove any individual to play a different strategy because, presumably, an agent representing that strategy would have tried it in the previous round. Within evolutionary games, the concept of an “evolutionary stable strategy” (ESS) was built on Nash’s equilibrium to define a state in which even if a small number of actors deviated from playing this strategy, the original mutual-bestreply equilibrium still would be reasserted. An evolutionary stable strategy is more robust than a Nash mutual-best-reply equilibrium because it generates a favorable outcome for its wielder even if a new mutant strategy attempts to invade the population.[623]John Maynard Smith introduces the concept of the evolutionary stable strategy as follows: “A ‘strategy’ is a behavioral phenotype; i.e., it is a specification of what an individual will do in any situation in which it may find itself. An ESS is a strategy such that, if all the members of a population adopt it, then no mutant strategy could invade the population under natural selection.”[624] Because the ESS is a game theoretic artifact, its definition is formal and its applications are mathematical.[625] Even though models with variables can graphically make a point for any set of actual values, to be fully applicable to concrete circumstances of animals maximizing fitness, an objective means to appraise value is needed.
One favored game for evolutionary game theorists is the Chicken game, aptly renamed Hawk-Dove. Dawkins supplies arbitrary values to make sense of applying game theory to evolutionary development: “Now as a purely arbitrary convention we allot contestants ‘points.’ Say 50 points for a win, 0 for losing, -100 for being seriously injured, and -10 for wasting time over a long contest.” Crucially, in evolutionary game theory, the reward structure of the game is proposed to translate directly into fitness value much as the first generation of game theorists assumed that individuals maximize money. Dawkins continues,These points can be thought of as being directly convertible into the currency of gene survival. An individual who scores high points, who has a high average ‘pay-off’, is an individual who leaves many genes behind in the gene pool.41
Nature plays the role of banker, so that the payoffs (or world states to which preferences refer in conventional game theory) are best thought of as objective survival criteria determined at a systemic level beyond an individual’s control or individual evaluation. Survival requires meeting specific objective needs enforced by natural processes. In this biological economy of competition for scarce resources, game theorists propose that the entities being selected for must optimize against each other precisely as noncooperative game theory stipulates and do not explore the possibility that after a threshold level of fitness value is acquired, organisms may cease seeking to gain more.
Selfishness, or individualistic optimization, is alleged to be a condition of nature perfectly captured by game theory. In Dawkins’s terms, “selfishness is to be expected in any entity that deserves the title of a basic unit of natural selection.”42 Game theory, originally applied to military strategy and subsequently to political economy, next proved a useful tool to apply to evolutionary biology. In turn, the apparent naturalness of noncooperative game theory to capture “the fierce competition for scarce resources in the relentless struggle to eat other survival machines, and to avoid being eaten” made it seem obvious that the game theoretic rational actor (here the selfish gene) exists prior to the theory discussing its behavior.43
Confident that nature hands out objective rewards for the fittest creatures, evolutionary game theorists are able to extrapolate to construct game theoretic payoff matrices to represent evolutionary interactions.
The selfish gene, which must optimize tangible rewards as a condition of existence in competition with others, is primordial. In biological terms, just as all physics ultimately must be consistent with the laws governing the actions of fundamental participles, all of life must conform to the dictates regulating the selfish gene. The natural processes acting on genes force them to comply with the axioms of rational choice theory, at least on an “as if” basis. Purposive action, if not intended, is mimicked.44 The pivotal point, on which the entire argument hinges, is that biological agents have objective needs structuring the payoffs of encounters. In Herbert Gintis’s words, “fitness maximization is a precondition for evolutionary41 Dawkins, Selfish Gene, 1976/2009, 70; see also 151. Note that even though it is presumed that nature grants objective value, evolutionary game theorists are not able to measure this value; thus, it is postulated for demonstration purposes. In 1976, Dawkins writes, “Unfortunately, we know too little at present to assign realistic numbers to the costs and benefits of various outcomes in nature” (75), to which he responds in 2009 that one good example of values “comes from great golden digger wasps in North America” (283). He does not mention the values or present any other cases of specific cost-benefit value to be plugged into ESS models, nor does he consider that fitness and survival may more accurately reflect a threshold value.
42 Ibid., 33.
43 Quote from ibid., 47, see also 67.
44 Ibid., 50-51, 196.
survival.”[626] Acting in accordance with the axioms of rational choice theory is a condition of survival under the assumption that rewards are directly correlated to an actor’s survival and reproduction prospects. Gintis further explains, “We can expect preferences to satisfy the completeness condition because an organism must be able to make a consistent choice in any situation it habitually faces or it will be outcompeted by another whose preference ordering can make such a choice.”[627] It is important to keep in mind that it is the presumption that objective needs dictate the unfolding of long-term evolutionary processes that makes it possible to apply game theoretic payoff matrices.
The payoff structure represents the nonnegotiable conditions hypothesized to be necessary to sustain life.After identifying the selfish gene as the elementary unit on which natural selection functions, many treatments of evolutionary game theory move seamlessly between the animal world and the human world.[628] Dawkins is clear in his statement of the confluence of evolutionary biology and human behavior:
My own feeling is that a human society based simply on the gene’s law of universal ruthless selfishness would be a very nasty society in which to live... Be warned that if you wish, as I do, to build a society in which individuals cooperate generously and unselfishly toward a common good, you can expect little help from biological nature.[629]
Dawkins suggests that the idea of the state of nature populated by selfish genes serves as a ubiquitous model, no matter whether the gene is in a single-celled organism or a person. It is impossible to exit the state of nature, and noncooperative game theory specifying the laws of individualistic optimization best captures this inevitable competitive struggle for existence. Gratuitous altruism or universalistic selflessness is not only not favored by nature but also would be rapidly exploited and hence displaced from a population.[630] The fundamental premise is that any expression of human behavior must comport with the inveterate imprint of genetic selfishness. The logic of noncooperative game theory and of the selfish gene are one and the same. Individualistic optimization is the only mode of action available. Under the assumption that the value agents must maximize as a condition of their existence is externally and objectively determined, cooperation is a persistent Prisoner’s Dilemma confronted by all organisms, and vying over territory is a Chicken game.[631]
Culture, or learned behavior not programmed into individuals’ genetic structure, is also presumed to obey the same rules of individualistic maximization. Dawkins coined the term “meme” to refer to “the new replicator... the idea of a unit of cultural transmission, or unit of imitation.”51 Examples of memes are “tunes, ideas, catch-phrases, clothes, fashions, ways of making pots or building arches,” yet memes are postulated to exist inside minds. In Dawkins’s words, “memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation.”52 Like genes, Dawkins’s memes have the properties of longevity, fecundity, and copying fidelity.53 Dawkins proposes that “just as we have found it convenient to think of genes as active agents, working purposefully for their own survival, perhaps it might be convenient to think of memes in the same way.”54 One example of a meme is the belief in God, understood to be a personal savior or almighty creator. Hinting toward his later work, The God Delusion (2006), Dawkins queries whether
the god meme... [has] become associated with any other particular memes, and... [if] this association assist[s] the survival of each of the participating memes? Perhaps we could regard an organized church, with its architecture, rituals, laws, music, art, and written tradition, as a co-adapted stable set of mutually-assisting memes.55
The concept of memes retains a fuzziness because unlike the phenomenon of DNA replication, which, arguably, has a specific site for identity and replication, cultural artifacts have a different ontology without a well-defined location for their existence. Whereas DNA exists in cells that replicate, memes, Dawkins suggests, exist as material entities in the world, yet propagate as a mind-virus “leaping from brain to brain.”
Regardless of whether the analogy between gene and meme is either fully intelligible or sound, its underlying point is to suggest that human culture operates according to the same laws governing biological reproduction. Just as natural scientists hold that the laws of physics must obtain everywhere in the universe, so, too, does Dawkins reason that the fundamental laws of biology must hold everywhere throughout the realm of living organisms. This idea that biological science is unified by the principle of replication which obeys the laws of game theory is profound.56 Dawkins ruminates,
What, after all, is so special about genes? The answer is that they are replicators. The laws of physics are supposed to be true all over the accessible universe. Are there any principles of biology that are likely to have similar universal validity? When astronauts
51 Dawkins, Selfish Gene, 1976/2009, 192.
52 Ibid., prior quote as well. Dawkins follows up in clarifying his meme concept in 2009, 322-323.
He admits that ultimately a meme would have to exist in terms of molecular brain structure.
53 Ibid., 194.
54 Ibid., 196.
55 Ibid., 197; see Dawkins, The God Delusion, 2008.
56 This is the leading insight in Herbert Gintis’s The Bounds of Reason, 2009. voyage to distant planets and look for life, they can expect to find creatures too strange and unearthly to imagine. But is there anything that must be true of all life, wherever it is found, and whatever the basis of its chemistry?... Obviously I do not know but, if I had to bet, I would put my money on one fundamental principle.[632]
To be sure that his readers have followed his message to this point, Dawkins emphasizes that this one fundamental principle is “the law that all life evolves by the differential survival of replicating entities.”[633] The gene serves this function for Earth-based life.[634] It is best modeled by noncooperative game theory, which holds that it must conform to these behavior assumptions as a condition for its successful survival and propagation.[635]
Dawkins’s original 1976 version of The Selfish Gene concludes that the game theoretic evolutionary stable strategy, or ESS, and noncooperative game theory require that individualistic actors must compete with one another on a momentary basis. As the next chapter discusses further, this vision of life holds that organisms must compete over scarce resources in a way best modeled as endless games of Prisoner’s Dilemma. Solving games with conflict is the fundamental problem of life. Dawkins draws The Selfish Gene to its conclusion:
A simple replicator, whether gene or meme, cannot be expected to forgo short-term selfish advantage even if it would really pay, in the long run to do so. We saw this in the chapter on aggression [with the Hawk Dove game]. Even though a “conspiracy of doves” would be better for every single individual than the evolutionary stable strategy, natural selection is bound to favor the ESS.[636]
Relying on game theoretic analysis, Dawkins concludes that the entire domain of biological action - cellular, organismic, and social - is composed of individualistic entities that must optimize an objective function in competition with others on a momentary basis. In a Prisoner’s Dilemma or a Hawk Dove (Chicken game), it would be better overall if agents peacefully cooperated. But this strategy is exploitable by defectors and aggressors who seek unilateral advantage in their apparently purposive struggle to survive and replicate.