Este Blogue é um estudo da Associação Projecto Raia Alentejana e tem como objectivo a discussão da violência em geral e da guerra na Pré-História em particular. A Arqueologia da Península Ibérica tem aqui especial relevo. Esperamos cruzar dados de diferentes campos do conhecimento com destaque para a Antropologia Social. As críticas construtivas são bem vindas neste espaço, que se espera, de conhecimento.

Guerra Primitiva\Pré-Histórica
Violência interpessoal colectiva entre duas ou mais comunidades políticas distintas, com o uso de armas tendo como objectivo causar fatalidades, por um motivo colectivo sem hipótese de compensação.

Tuesday, 13 April 2010

‘Heroism’ in Warfare as a Functionally Specific Form of Altruism.

Oleg Smirnov
Political Science, University of Miami
Holly Arrow
Psychology, University of Oregon
Doug Kennett
Anthropology, University of Oregon
John Orbell
Institute of Cognitive and Decision Sciences
University of Oregon

Authors’ Note: We thank James Fowler, Warren Holmes, Timothy Johnson, David Osborn,
Frances White, members of the “Warfare and Killing” spring 2006 seminar and several
anonymous reviewers for helpful comments on earlier drafts. We are also grateful to members
of the Evolution Focus Group of the Institute for Cognitive and Decision Sciences for helpful
feedback after early presentations of this project.

“Heroism” in Warfare
As a Functionally Specific Form of Altruism.

“When two tribes of primeval man, living in the same country, came into competition, the tribe
including the greater number of courageous, sympathetic and faithful members…would without
doubt succeed best and conquer the others.” Darwin, The Descent of Man, chapter 5, p. 156.

We use two simulations to explore the possibility that heroism (risking one’s life fighting for the
group) evolved as a specialized form of altruism, selected as a result of warfare through humans’
ancient past. In the first simulation, altruism as a general disposition promotes all forms of
altruistic behavior, including heroism. In the second, heroism and communitarianism (altruistic
actions beyond warfare) are separate, domain-specific dispositions. Warfare selects weakly for
altruism, more strongly for communitarianism, and substantially for heroism. Heroism evolves
more readily when groups are small and mortality in defeated groups is high—features plausibly
characteristic of humans’ ancestral past.

When Homer asks in the Iliad “What god drove them to fight with such a fury?” he was
posing a question that remains problematic three thousand years later: What makes soldiers
willing to fight at great personal risk for their polis, their tribe, their ethnic group, or their
country? There is no doubt that soldiers often do fight in this manner; the history of warfare is, in large part, the history of ordinary men (and, in recent times, women) who willingly confronted the risk of death when fighting for their tribe, polis, country, or other group. In the present paper we call this behavior “heroism.” Heroism is well recognized as a potential human behavior, but the existence of heroism is most commonly treated as a background assumption in examining the nature of war. In this paper we address what we see as the central puzzle of heroism: How could it have evolved?
Most studies that address heroic actions in warfare have focused on “proximate”
answers—emotional, cognitive or other mechanisms that prompt such behavior in the here and
now. Thus, for example, loyalty to small groups of fighting comrades (Gat 1999; Shills and
Janowitz 1948; Stern 1995) or, perhaps, a regiment (Holmes 1985), the rage and fear provoked
by an attack, or threat of an attack, against one’s own group (Horowitz 2001), and cognitive
errors such as overconfidence about the risks involved in heroism (D. D. P. Johnson 2004; D. D.
P. Johnson et al. 2006; Wrangham 1999b) have all been argued to support such behavior. By the same token, social psychologists have identified many mechanisms likely to be implicated in
humans’ frequent xenophobic willingness to engage in hostile action against other groups—most
famously, the ease with which we categorize others into “in-group” and “out-group,” favoring
the former and, often, demonizing the latter (Ackerman et al. 2006; Rothbart and Lewis 1988;
Rothbart and Taylor 1992; Tajfel and Turner 1979).
But this level of explanation, while certainly compelling, is only one level of explanation,
the other being the “ultimate” or “evolutionary” processes that selected for such proximate
mechanisms through evolutionary time. Most theorizing in the social sciences invokes only
proximate mechanisms, but such mechanisms must have evolved via some evolutionary process of selection on genes, on cultural patterns, or on gene-culture interactions (Boyd and Richerson
1985; Odling-Smee, Laland, and Feldman 2003; Richerson and Boyd 2005). A complete
explanation of the behavior in question should thus consider both proximate and ultimate
causation. Here we focus on the latter: How could mechanisms supporting “heroism” have
been positively selected during humans’ ancestral past? By definition, heroism involves a
fitness cost to the individual (via increased risk of death), hence we might expect it to be selected against, eventually disappearing from the human population. Yet heroism certainly does happen
with some frequency across a wide variety of cultures, suggesting that it is a species typical trait. How could this have come to be?
One standard answer is Hamilton’s (1964) famous explanation of how altruism in general
might have evolved. Hamilton turned attention to the selective fate of genes rather than of
individuals per se, pointing out how sacrificial action by one individual could result in genes
supporting that act spreading more rapidly than had the individual acted selfishly—as long as the beneficiaries of such action were appropriately close relatives.1 Inclusive fitness has been
invoked by Alexander (1979), Masters (1983), Shaw and Wong (1989), Thayer (2004), van der
Dennen and many others, in attempts to understand the genetic basis of humans’ propensity to
warfare and, using our term, therefore to heroism.2 The general point is that, during humans’
remote ancestral past groups were, most probably, comprised largely of quite close kin, making a disposition toward sacrificial action on behalf of the group an attribute that could evolve, despite adaptive costs to the individual per se.
Importantly, this account explains heroism as a product of the same ultimate, selective
processes that might produce any other altruistic behaviors. Sharing meat from a hunt, for
example, could be explained as readily as fighting for one’s group in a battle with other groups.
The account nicely combines a plausible reconstruction of family-based social organization in
our ancestral past with a foundational idea in modern evolutionary biology. It is also consistent
with the pervasiveness of kinship rhetoric—the “fatherland, “band of brothers” etc—in modern
warfare (G. Johnson 1987). It is quite plausible that the particular form of altruism that interests us, heroism in defense of one’s group, evolved via the combined impact of multiple processes
that have been invoked for explaining altruism in general—including kin altruism, reciprocity in
exchange relationships (Axelrod 1984; Trivers 1971) and multi-level selection (most notably,
Sober and Wilson 1998).3
Here we develop the possibility that, even without the impact of kin altruism and
reciprocity, heroism could have evolved as a “domain specific” form of altruism in response to
warfare in our ancestral past. The idea that human cognitive architecture consists, in substantial
part, of functionally specific information processing modules is widely accepted in evolutionary
psychology and in cognitive neuroscience more broadly, although scholars differ in arguing for a
strong version of modularity (notably Cosmides and Tooby 1994; Hirschfeld and Gelman 1994;
Sperber 1994) or for a combination of specialized modules and some more general functionality
(notably Buller 2005; Fodor 2000; Mithen 1996). The standard strong modularity argument is
given by Cosmides and Tooby (1994 p. 89) as follows:
…different adaptive problems require different solutions… Speed,
reliability, and efficiency can be engineered into specialized mechanisms
because there is no need to engineer a compromise between competing task
demands…As a rule, when two adaptive problems have solutions that are
incompatible or simply different, a single general solution will be inferior to
two specialized solutions.
However this argument plays itself out (for a constructive appraisal see Barrett
and Kurzban 2006), the extensive literature on human altruism has, to our knowledge,
focused exclusively on the problem of how a generalized disposition to altruistic
behavior might have evolved. The possibility that multiple, domain specific altruistic
dispositions might have evolved independently, each in response to a distinctive
adaptive problem and each producing, therefore, at least somewhat different proximate
mechanisms appears to have been overlooked. Since heroism is, by our definition, an
altruistic response on behalf of one’s group in the event of war with some other group,
its task demands would appear prima facie quite distinct from those of other altruistic
behaviors (e.g., providing food to others and caring for the sick). This makes it
plausible that heroism could have evolved on its own distinct trajectory, independent
of such other forms of altruism, and with warfare as the agent of selection.4
Warfare is a group-level phenomenon, and its broad outcomes (victory, defeat,
and standoff) are also group-level phenomena. Accordingly, all group members—those
who fight as well as those who do not—can suffer “genetic death” should the group be
defeated.5 However, the consequences of group-level outcomes can differ among the
individuals comprising such groups. Most obviously, those who fight in the group’s wars
run an increased risk of dying as a result, reducing the probability that their genes will
pass on to the next generation. Should the group be victorious, survivors stand to benefit
significantly, but heroes are less likely to be among those survivors. Along with males’
sexual access to females from the defeated group (viz: rape, captured concubines etc.),
the spoils of victory can include access to the defeated group’s territory and whatever
resources that territory contains. Clearly, frequent warfare during humans’ ancestral past
could have had major adaptive consequences—positive and negative—for individuals in
the warring groups.6 Since heroism as we have defined it is central to the outcome of
wars, the evolution of heroism is a good candidate for being among those consequences.
How frequent was warfare in our ancestral past? Attempts to answer this question
have provoked a good deal of controversy. Some accounts of the archeological record
suggest that war was quite frequent. LeBlanc (2003, pp. xii - xiii) comments:
Just how common was warfare in the past? I have finally concluded that
warfare was quite common… and that my findings on three continents and
within multiple time periods were not a fluke but the norm. This has led me
to reason that if conflict was common, then it must have been an important
occurrence in the course of human history. (Italics in the original.)broadly, “coalitional violence”—has been present, at least to some extent, throughout our
ancestral past, and our question is whether warfare, happening with any significant frequency,
could have selected for heroism. The simulations that we will now describe allow us to study the
relationship between frequency of warfare and such selection, and we will report findings to that
effect later in the paper.

Two Simulations
In the first simulation, altruism is domain general, promoting: (1) communitarianism—a
group-benefiting behavior that increases the mean fitness of group members but does not involve
fighting enemies; and (2) heroism a behavior that benefits the group by contributing to its
success in warfare. In the second simulation, these two behaviors are promoted by two domain
specific attributes that are free to evolve independently. A formal description of the two
simulations can be found in Appendix 1 which is available on the Journal’s website; here we
provide a verbal account of the simulation’s key features.
Model 1: Domain general altruism
Groups and resources. Four groups each occupy a fixed resource base on which its
members are critically dependent for nourishment. The size of the resource base for each group
is a parameter; it can vary across groups but not across time and sets a limit on sustainable group size.
Altruism. Each group member has a propensity to behave altruistically, which is modeled
as a continuous variable with values between 0 (never) and 1 (always). The starting mean
altruism of each group is a parameter of the model; the altruistic propensity of a group’s
members varies in a uniform distribution centered at the specified mean. An individual’s
altruism increases the reproductive success of all group members and contributes to the group’s
success in warfare as a function of that individual’s altruism score (the more altruistic, the more
benefit to others across both domains); the reproductive cost paid by the individual is similarly a function of that score (the more altruistic, the greater the cost to self).
Baseline Fertility and Individual Reproduction. Baseline fertility is the probability of
each group member’s having an offspring in a given generation—prior to any adjustments based
on the incidence of altruism in the group (the more altruism summed across all group members,
the greater each group member’s probability of reproducing), the individual’s own altruism score (the greater that score, the smaller the probability of that individual’s reproducing), or the
outcome of war (group members who do not survive wars do not reproduce). Should there be
more than one war in a generation, the cost of participating (reduced probability of surviving to
reproduce) is assessed separately for each.
Going to War. A group goes to war when its population exceeds the carrying capacity of
the resource base—that is, when the resource base per capita drops below a specified threshold.
At this point the only way a group can support its members is to capture the resources held by
another group. Target groups are chosen at random, with any group that is attacked by another
having to defend itself by fighting.
We recognize, of course, that competition for scarce economic resources is not the only
factor that increases the probability of war; this is merely a simplifying assumption for the
"generic" wars of our model. Chagnon (1988) and others, for example, point to the frequency
with which capturing females is the stated reason for hunter-gatherers going to war, and females are obviously a reproductively significant “resource” (Trivers 1972). It is also the case that
particular wars may have highly visible “triggering events” (the seduction of Helen, the
assassination of the Archduke Ferdinand). This is not, however, inconsistent with an ultimate
explanation in terms of population pressures on groups’ resources (Shaw and Wong 1989, p.11).
Helen’s seduction, for example, took place during a time of mounting economic competition
between the Trojans and the Greeks. Certainly, there must have been a complex relationship
between capturing land and capturing females motivating our ancestors to go to war—as
suggested by Betzig (2005, p. 335) in her analysis of the Biblical case as recorded, among other
places, in Deuteronomy 20:13-17:
God handed Moses two different laws about spoils. One was for wars with
close neighbors; the other was for more remote wars. When their enemies
lived far away, he said, ‘you shall put all the males to the sword, but the
women and the little ones, the cattle, and everything else in the city, all its
spoil, you shall take as booty for yourselves.’ But when their enemies lived
nearby, ‘you shall save alive nothing that breathes, but you shall utterly
destroy them.’ Land was the limiting factor.
The assumption on which our model is based—that resource scarcity leads to
war—is perfectly compatible with the capture of female reproductive capacities as one
among many proximate causes of war. The idea that land, thus somatic resources, was
a critical “limiting factor” is, nevertheless, widely assumed among anthropologists,
biologists, ethologists, political scientists, psychologists, sociologists and others
addressing the causes of ancient warfare (e.g. Alcock 1978; Carneiro 1970; Durham
1976; Eibl-Eibesfeldt 1979; Kennett et al. 2006; Kennett and Kennett 2000, 2006;
Lambert 1997; Lambert and Walker 1991; Shaw and Wong 1989; Thayer 2004; van
den Berghe 1978; Wilson and Wrangham 2003) and we adopt it here.
Victory and Defeat. The group with the highest summed altruism score wins. This
represents the total amount of heroic fighting available within each group. Consistent with the
“imbalance of power” hypothesis developed by biologists and primatologists (Alexander 1979;
Wrangham 1999a)—as well as with Napoleon’s comment that “God is on the side of large
armies”—the larger group will win when the mean propensity to altruism is equal across two
contending groups. However, a smaller population can defeat a larger one if its members are
substantially more altruistic (hence more heroic).
Death. Some proportion of the defeated group is killed. We will report our simulation
findings from the strong assumption that all are killed, so that defeated groups are eliminated
from the evolving population. While this extreme assumption is certainly consistent with some
examples from the historical record (Potidaea, Mytilene, and Melos in the Peloponnesian war,
for example), the proportion of a defeated group that is killed is an important parameter, to which we will return in a later analytic section (specifics are available on the Journal’s website). In the simulation, members of the victorious group migrate to the newly captured territory such that per-capita resources in the two areas are equalized. Once migration is complete, no “memory” of prior ties persists, so the two “daughter” groups created by the schism are just as likely to attack one another in subsequent rounds as they are to attack a different group.
Variation. Selection on altruism—as on any other attribute—can, of course, only happen
in the context of variation on that attribute. As noted, members of each group vary in altruism at the start of the simulation. During reproduction, variation is maintained by two mechanisms.
One models random mutation (defined as 1 M in the appendix on the Journal’s website); by
default, it occurs here in less than one percent of offspring, and can result in the offspring having
an altruism level quite different from the parent. The other mechanism (defined as 2 M in the
appendix) simulates (without directly modeling) sexual reproduction, such that offspring
resemble their parent within a range of variability.
Model 2: Domain specific with both “communitarianism” and “heroism”
The second simulation has the same general structure, except that each individual now
has two domain specific altruistic propensities, heroism and communitarianism, each similarly
modeled as varying between 0 and 1. Starting mean heroism and communitarianism for each
group are separate parameters of the model. Member levels for the two attributes are
independently drawn from a uniform distribution centered at the specified mean. Reproductive
costs from communitarianism are paid every generation; those from heroism are paid per war.

We ran 10,000 simulations of each of the two models. To ensure that the data we report
reflect a wide variety of possible evolutionary environments, the following parameters were
drawn randomly7 for each run:
1. Each group’s resource endowment ( g R )—specified separately for each group;
2. Baseline fitness—the probability of reproductive success for all agents before the
consequences of altruism, communitarianism, heroism or warfare are incorporated ( b P );
3. The fitness advantage to group members from an individual’s communitarianism ( c P );
4. The cost to the individual agent of its own communitarianism ( C C );
5. The cost to the individual agent of its heroism ( H C );
6. (In Model 1) Mean starting altruism ( A S );
7. (In Model 2) Mean starting communitarianism and heroism ( C S , H S );
8. The two sources of variation (two types of mutation) in the attributes of offspring as
specified in the appendix ( 1 M , 2 M ).
Two parameters were fixed across all the simulations: the survival threshold, T =1 (one unit of
resource per capita), and the number of groups, which was four.
Each of the 10,000 simulations was run for 1100 generations, allowing a sufficient
number of generations for the system to evolve away from diverse starting values. For the last
100 generations we recorded the moving average of altruism in the domain general model, and
of communitarianism and heroism in the domain specific model. The simulation parameters
(which varied across runs as described above) and the frequency of wars across all generations
(an emergent variable) were also recorded for each simulation. In a smaller sample of runs to
check for the system’s sensitivity to some of our choices, we increased the number of
generations and varied both the number of groups and the length of the moving average across
which we recorded data. None of these modifications affected our results.

With the domain general model we observed a modest but significant selection on
altruism. This is shown in Figure 1, which is a frequency distribution for evolved altruism. The
horizontal axis specifies the altruism level averaged across the last 100 generations of the 10,000 simulations and the vertical axis records the density of cases across the randomized parameter space. The mean altruism value in this positively skewed distribution is 0.25 (the median is 0.17), interpretable as the mean individual being 25% altruistic—or, alternatively, that the mean individual would have a .25 probability of contributing to group members’ fitness via its communitarian activities and a .25 probability of fighting heroically in any war.
Despite the fact that both behavioral consequences of general purpose altruism are
reproductively costly to individuals, therefore, we do observe some selection on that attribute.
Agents pay a reproductive cost proportional to the strength of their generalized disposition to
altruism, but this cost is outweighed by the benefits that individuals reap from their group’s
success in warfare. Multiple regression of ending altruism values on parameters in the model
(see Appendix II on the Journal’s website) shows a negative association between evolved
altruism and (1) the cost of altruism; (2) the average size of group resource bases (hence, the
average size of groups); and (3) variation in resource base size (hence, variation in size among
the groups); it also shows a positive association between altruism and the frequency of war. This
suggests that higher (and less typical) evolved values of altruism occurred in simulation runs
where the personal cost of altruism was low, where groups were smaller and more equal in size,
and where wars were quite frequent.
With the domain specific model, in which communitarianism and heroism were free to
evolve as separate attributes, Figures 2a and 2b show that: (1) heroism evolved to substantially
higher levels than communitarianism with means of 66.9% and 30.5% respectively and medians
of 70.3 and 22.6 respectively; (2) both attributes evolved to significantly higher levels than did
altruism in the domain general model. There are, therefore, three findings to be explained—first, the fact that there was some positive selection on general purpose altruism, despite its costs to the individual; second, that there was stronger selection on heroism than on communitarianism
despite their respective costs; and third, that when communitarianism and heroism are free to
evolve separately, both evolve to higher levels than when they are combined as expressions of a
single, general purpose altruism attribute. We will address the evolution of general purpose
altruism shortly; first we discuss the relative evolution of the two domain specific forms.

Why does heroism evolve to higher levels than communitarianism?
In our model heroism is only costly in the event of war. Given that war only occurs
periodically—in the simulations any given group goes to war with a probability of about .5 per
generation—while communitarianism occurs in every generation, perhaps heroism evolves to a
higher level simply because the cost of heroism is paid less frequently than the cost of
This does appear to be part of the story. Figure 3 reports the distribution of heroism
when its cost is paid every generation rather than per war. With the mean of this distribution
now at .475 (as opposed to .669 in the original domain specific model), clearly this cost
difference accounts for some of the relatively greater selection on heroism. Across the range of
parameters, it appears that selection on heroism is stronger when such behavior is not invoked
every generation, as is communitarianism. But that is only part of the story, since the mean of
heroism is still substantially higher when it is evoked every generation than is the mean of
communitarianism (.305) when it, too, is evoked every generation.
Another part of the story concerns the immediacy of the military benefits a group reaps
from communitarianism and heroism. Since reproduction happens at the end of each generation,
communitarianism increases the number of fighters a group will be able to field in the next
generation while heroism increases a group’s fighting capacity in the present one. Thus
communitarianism can only increase a group’s future fighting ability—assuming the group
survives any wars in the current generation, which will depend on group size and heroism now.
The delayed effect of communitarianism is, of course, consistent with real-life population
dynamics: since infants and young children confer no advantage in war, the war-fighting
benefits of increased fertility cannot be realized immediately.
Communitarianism is also a “double-edged sword” for a group’s fighting ability. While
larger groups are more likely to win wars, high population growth can also be responsible for
getting a group into war in the first place (faster population growth means that a group reaches
its carrying capacity more rapidly), when, in a war, there is some chance of its losing, thus of
selection against communitarianism. Heroism, on the other hand, is an unambiguous good for a
group. In the absence of war, and assuming its cost is only paid in the event of war, it does no
harm to the individual or the group, but in the event of war it can be decisive for victory.
Ultimately, selection on communitarianism and on heroism must be a function of whether
the behavior produced by those dispositions is “critical” to the group’s success in warfare—thus
to the individual’s survival and reproduction—and while both contributions might be critical for
the outcome of a given war, heroism is more likely to be critical than communitarianism.

Why, then, does altruism evolve?
The positive selection on general purpose altruism in the single attribute model, modest
as it is, can now be explained in the same way as selection on heroism and communitarianism in
the two attribute model. Altruists fight for their groups, and a given altruist’s fighting can be
critical for the group’s survival, thus for the altruist’s own survival. Similarly—although with a
lower probability—an altruist’s communitarian behaviors might also be critical for such survival
via the role that numbers as such can play in outcome of wars.

Why do communitarianism and heroism evolve further than general-purpose altruism?
An unexpected finding was that when heroism and communitarianism are free to evolve
independently, both evolve to higher levels than does the single, general purpose altruism.8 What accounts for this?
In retrospect, at least, the explanation is clear. When a single, general purpose mechanism
performs two distinct functions (A and B) both of which decrease individual fitness, selection
against that mechanism based on the costs of A will also select against B, and vice versa. The
general purpose capacity will, in other words, pay a cost whenever either of the two behaviors is
invoked. Conversely, when distinct, special purpose mechanisms are dedicated to A and B,
selection based on the individual costs of B has no implications for selection based on the costs
of A, and vice versa. Thus, breaking the general purpose mechanism down into two special
purpose mechanisms means that the evolution of one attribute is not handicapped by the cost of
the other. Notice that heroism, invoked only every second generation or so, benefits more from
such “de-linking of costs” than does communitarianism.
This finding points to the cost-benefit logic that could support a modular design for the
evolved “cognitive architecture of altruism.” The degree to which propensities for different
forms of altruistic behavior are, in modern humans, actually correlated (positively or negatively) is, of course, an empirical question awaiting investigation by other means than computational
modeling. Also, findings from the model do not resolve the general problem of how privately
costly altruistic dispositions (whether unitary or multiple) actually did evolve. Each disposition
must still be positively selected despite the costs that it generates for the acting individual.
Nevertheless, the finding does raise the possibility that thinking about altruism as a bundle of
special purpose forms of altruist behaviors—each evoked in some circumstances but not in
others—and not as a single general purpose disposition evoked regardless of the contextual
specifics, will prove a fruitful path to follow. Whatever they might be, selective pressures
favoring special purpose altruisms (plural) would not have to be as strong, ceteris paribus, to
overcome the associated costs as would selective pressures favoring general purpose altruism
(singular) if the behavior in question were to evolve.
The case for humans’ past being one of “constant battles” becomes increasingly difficult
to make the further back in time one looks and, as discussed above, this has fueled arguments
about just how “constant” warfare actually was in our ancestral past. While those arguments are
for archeologists to resolve, as shown on-line in Appendix II, in our simulation the frequency of
warfare does positively predict selection on altruism in the first model, and on communitarianism and heroism in the second one.9
One strong assumption of both simulations is that all members of defeated groups are
killed. To examine what happens when this is relaxed, we turned to an analytic model.

An Analytic Model of Heroism
Although our simulations make a range of simplifying assumptions, they are still more
complex than what can be readily modeled analytically. Accordingly, we employed a simplified
analytic model to explore more rigorously the impact of a few key parameters on the evolution of heroism.10 The cost of this precision was to reduce the number of groups from four to two
equally sized groups and to model heroism as a dichotomous variable with each agent being
either fully heroic or a complete coward. (Appendix III on the Journal’s webpage contains a
formal description of the model.)
As noted above, the simulation results are based on the strong assumption that a defeated
group is entirely wiped out. Although the archeological record does suggest that genocide was at
least sometimes practiced (Keeley 1997; LeBlanc and Register 2003) and the elimination of a
competing group has been documented in a chimpanzee population (Wilson and Wrangham
2003), we simply do not know just how pervasive this actual outcome was. What happens when
the simulation’s genocide assumption is relaxed?
In the analytic model, any individual’s probability of surviving a war is defined by 1 –
dG, when d is the probability of the group’s being defeated (a function of the relative summed
heroism scores in the two contending groups) and G is the proportion of the defeated group that
is killed (the genocide parameter). At one extreme, therefore, if the genocide parameter were 1.0 and the entire defeated group is to be killed, then an individual hero’s actions would be critical if the two warring groups were otherwise equal in their summed heroism scores—critical not only for the group’s survival, but also for the hero’s own survival. At the other extreme with the genocide parameter at zero, all individuals survive the war despite their defeat, meaning that a hero’s action, while costing him personally, does nothing to promote his own survival. It
follows, therefore, that as G increases, the probability of an individual’s heroism rebounding to
his own advantage also increases. Figure 4 shows the proportion of heroes q* as a function of
the G parameter across three different population sizes11 when, in equilibrium, it is equally
beneficial to be a hero or a coward. (See Proposition 3 and related proof in Appendix III on the
Journal’s website.) As population size increases from 50 through 100 to 200, the slopes of the
curves flatten out and the equilibrium proportion of heroes for a given level of the genocide
parameter is reduced.
In summary, selection on heroism in the context of warfare is governed by two
parameters, genocide and group size: (1) The larger the proportion of the defeated group that is
killed, the more critical a hero’s action likely will be for his own survival and reproduction, thus
for selection on heroism; (2) The smaller the group, the more likely it is that any given
individual’s heroic action will be critical to the group’s survival, thus again for his own survival
and for selection on heroism.

Summary and Conclusions
Using simulation, we have demonstrated that heroism—a willingness to fight for one’s
group even when it places oneself at a reproductive disadvantage relative to other group
members—can evolve based on the selective pressures of war within a population of groups that, t least sometimes, go to war with each other over scarce resources needed for individual and
group survival. In the first simulation agents are characterized by a general purpose altruism
(supporting both “communitarianism” and “heroism”) and there is modest positive selection on
that attribute. When agents are characterized by the two independent, special purpose attributes heroism and communitarian, however, both of those attributes evolve to higher levels than general purpose altruism, with heroism evolving to substantially higher levels than
communitarianism. All three attributes evolve insofar as the individual’s action, while
personally costly, can increase the possibility of the group surviving a war, therefore of the
individual’s also surviving—and thus of reproducing.
We have also shown that heroism is particularly likely to evolve when group size is small
and when the casualty rate for defeated groups is high. The ecological validity of the first of
these parameters is, of course, compatible with the accepted fact that our remote ancestors did
live in quite small groups (Dunbar 1993, 1996), but the second is more problematic. On the one
hand, capture of reproductively valuable females would have reduced the death rates of defeated groups, allowing some gene flow between defeated and winning groups. On the other, the probability of most or all members of a defeated group being wiped out would, surely, have been higher in small groups than in larger ones. This said, however, the analytic model does
demonstrate that complete genocide is not necessary for heroism to evolve. It can still do so—
albeit, to lower (and we expect more realistic) levels—with substantially less draconian
outcomes to warfare.
Our findings with respect to the possible impact of war on heroism are not incompatible
with heroism also evolving in response to Hamiltonian (1964) inclusive fitness. Heroism
certainly could have evolved among (small) kinship groups in which members fought in
response to threats to their kin. But our results suggest that heroism could also have evolved as a consequence of ancient warfare even absent close kinship among groups’ members. In fact,
attention to the proximate mechanisms we sketched at the outset suggests a complex interaction among the respective mechanisms. If kinship were all that mattered, we would expect that people drawn into modern, large-scale wars would be less easily “fooled” into risking their lives for a group of strangers by mere kinship rhetoric. On the other hand, if the processes we have identified were all that mattered, we would expect such kinship rhetoric to be irrelevant—which it is not. Clearly, further research is needed to investigate the relative contribution of these different selective forces.
Does our model “take the heroism out of heroism” (cf. Trivers 1971)? At the ultimate
level at which we are working, it does. This can be seen by considering the extreme case where
group size is reduced to one (the acting individual) and the genocide parameter is set at 1. Here
the individual is unambiguously fighting solely for his own life. While increasing group size
beyond that does produce other beneficiaries, selection still happens on heroism only to the
extent that an individual’s heroism is critical for his own survival—and thus can offset the
reproductive costs the hero must pay relative to other group members who benefit from his
action without having to pay them.
But, of course, most heroes are, no doubt, responding to particular emotions and
cognitive processes, not running such “private fitness accounting equations” in their heads.
Hector in front of Troy, for example, could have been motivated by knowing that only he had
any chance of defeating Achilles and, therefore, of saving his own life. But there is nothing of
that in The Iliad. On the contrary, the story makes it clear that he was responding not only to
fear for his own life—which he clearly does experience—but to his love of Troy, loyalty to his
comrades, honor and, perhaps in the end, to overconfidence that led him to think he did have a
chance of defeating Achilles. It is his response to those proximate emotions and beliefs that
justifies his status as a hero, not the evolutionary logic that, over thousands of previous
generations, produced those things in his particular, unfortunate circumstances.
Our finding that communitarianism and heroism, when modeled as separate, domain
specific attributes, both evolve to higher levels than domain general altruism has, we believe,
implications for research addressing the evolutionary roots of altruistic behavior in general. It
does not, of course, mean that the standard problem of “compensating” altruism for the private
costs individuals incur in performing altruistic acts is resolved. Models of how domain-specific,
special purpose altruistic dispositions might evolve must still respond to that problem—as,
indeed, our model has for heroism and communitarianism. Nevertheless, to the extent that
altruisms (plural) will evolve to higher levels when their costs are decoupled, we would expect
natural selection to favor such decouplings.
How far such decoupling might proceed would depend, of course, on the particular
design efficiencies to be gained by decoupling, and we might expect at least some limits in this
respect as well as complementaries at the proximate level (and, presumably, also at the neural
level). In general, however, our findings suggest that empirical research might profitably turn
attention toward identifying how different forms of altruism evolve differently across different
domains—a move that, once again, will surely be more successful if conducted with an explicit
sensitivity to both ultimate and proximate causation.
If the propensity for heroism in war is, indeed, a species typical attribute of humans as
our findings suggest is possible, does that condemn us to a future of “constant battles”? Our
model does not address that question. In that model, war is triggered by resource stress, but that is only an assumption (plausible, we believe, in light of the archeological studies cited earlier) not a finding. An answer to the question, then, depends on the particular proximate emotions and cognitive processes that provoke heroic action in the here-and-now, and whether those could, in themselves, also provoke warfare—not only among our ancestors, but also among
ourselves and our descendants.

1 Hamilton’s rule is that altruism can evolve under the condition rb > c, that is when the benefit
to the recipient (b) multiplied by the relatedness of the recipient to the altruist (r) is greater than
the cost (c) to the altruist.
2 The list includes Sir R. A. Fisher who, in his foundational work The Genetical Theory of
Natural Selection (1930, p. 163), addressed the problem of “heroism” in tribal societies finding a
solution in terms that anticipated Hamilton’s relatedness-based theory of altruism.
3 Various authors have discussed the ways in which mechanisms that have been presented as
conceptually distinct might be subsumed by one another. For example: Sober and Wilson
(1998) see kin selection as being subsumed by multi-level selection; Reeve (2000) sees Sober
and Wilson’s model as a special case of Hamilton’s equations, and Humphrey (1997) sees kin
selection and reciprocity as generalizing into a single broad principle.
4 The term “Heroism” is commonly used more broadly. Becker and Eagly (2004), for example,
examine “heroism” exhibited by Carnegie medalists, by non-Jews who risked their lives to
rescue Jews during the Holocaust, by kidney donors, and by volunteers for the Peace Corps and
Doctors of the World. Here we restrict the term only to altruistic action in warfare.
5 We do recognize that female non-combatants who survive a war are historically less likely to
be slaughtered than are males. For simplicity here, however, we do not address possible
differences between males and females in the evolutionary consequences of warfare.
6 A growing literature has addressed multi-level selection on normative systems and
institutions, some of it paying particular attention to warfare as the agent of selection. Soltis,
Boyd and Richerson (1995), for example, used the extensive ethnographic literature on New
Guinea to assess whether warfare and associated group extinctions had been sufficiently frequent
to account for the evolution of group-benefiting normative and institutional patterns, concluding
that it had not; for such selective processes to have significantly influenced even one such group
attribute, between 500 and 1000 years would have been necessary. Other work assessing the
selective impact of warfare in multi-level terms includes Dawson (1999) and Richerson and
Boyd (1998); a foundational work on multi-level selection is Sober and Wilson (1998). For
critical assessments of multi-level selection, see Reeve (2000) and Maynard Smith (1998). In the
model to be developed here, groups can live or die as a consequence of warfare, but individual
attributes are what replicate, with the individual’s behavior potentially being critical for the
success and survival of the group, thus for replication of his own attributes.
7 From a multivariate uniform distribution with an identity correlation matrix with
~ U[50,100] g R , ~ U[0,0.5] b P , ~ U[0,0.5] C P , ~ U[0,0.1] C c , ~ U[0,0.1] H c , ~ U[0,1] A S ( C S ,
SH for the two attribute model), ~ [0,0.005] 1 M U , ~ [0,0.05] 2 M U . Notations specified here
are employed in the formal statement on the Journal’s website.
8 Mean evolved communitarianism and heroism values have a zero correlation. Hence there
was no tendency for something akin to generalized altruism to evolve in the second, domain
specific model; nor was there evidence for agents to “specialize” in a particular form of domainspecific
9 Other key input parameters such as cost of heroism, the size of groups’ resource bases, and
variation in the size of groups’ resource base were all significant negative predictors of heroism.
10 In our simulation, genocide in the event of defeat is the only way that agents die. Reducing
the level of genocide in the simulation produced exponential population growth and constant
war—along with a vastly increased demand on computational resources. With G = 1, however,
population size remains more or less constant, cycling around the same mean. Accordingly, for
the analysis of genocide and population size, we have relied exclusively on the analytic results.
11 In the analytical model with the total population consisting of two groups, the curves in
Figure 4 correspond to group sizes of 25, 50, and 100. In the simulation runs reported above (in
which G =1), the average resource base size (which constrains group size) was 75 (and ranged
from 50 to 100), with mean evolved values of heroism of .475 and .669, depending,
respectively, on whether the cost of heroism was paid per generation or per war.

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Figure 1.
Frequency distribution of evolved altruism in the one-attribute model. Mean altruism =

Figure 2a.
Frequency distribution of evolved heroism in the two-attribute model. Mean heroism =

Figure 2b.
Frequency distribution of evolved communitarianism in the two-attribute model. Mean
communitarianism = 0.305.

Figure 3.
Frequency distribution of evolved heroism in when the cost of heroism is paid every
generation. Mean heroism = 0.475.

Figure 4.
Equilibrium proportion of heroes q * across two groups as a function of genocide G for
three different population sizes n, 0.5 b P = , c = 0.05 .

1 comment:

Numa terra lá distante said...

In my opinion:
Inclusive Fitness-Heroism-Duel