Humans behave according to the rules of selfish myopic rationality, most of the time, in preference to the other possibilities, which do occur, but more rarely: (1) The instinctive-impulsive mode. (2) The random-uncoordinated mode. (3) The long-range supra-rational mode. (4) Maximizing “extended fitness” a la sociobiology (family loyalty). (5) The altruistic compassion-empathy mode. (6) The deliberately or unintentionally self-destructive mode.

Nations, to the extent to which they can be visualized as unitary actors (i.e. internally integrated by some kind of consensus or at least a tacit consent of important constituent parts) also act mainly as myopic selfish rational decision-makers. This includes decisions for peace or war. However, when two nations interact in a dyad, the results of the bilateral myopic rationality are sometimes far from what cost-benefit calculations would seem to indicate, because of the complex dynamics of the interaction. This is why we can speak of the “causes” of war rather than the “reasons” for war; thinking of the driving forces as a push from behind (in time), rather than a pull toward a future goal. That is, in Aristotle’s terms, we think of “efficient causes” rather than of “final causes”. Sure enough, living conscious agents are deciding, but they are at least partly driven by the dynamics of situations.

Murray Wolfson et al. (“Non-linear Dynamics of International Conflict”, paper for Peace Science Society International, University of Michigan, Ann Arbor, 1991) found that war in a dyad of nations is at low values of occurrence frequency (local minima) when either a) parity in weapons or power exists between them, or b) when one of them has great preponderance of power. (There have been controversies among political scientists for a long time about which condition is more favourable for absence of war. It seems that both are right.) In the intermediate condition c), when the power ratio favours one side somewhat but not too much, the computer simulation yielded wave-like oscillations, perhaps due to the ambiguity of perception of the situation. At the stable states a) and b), there is a single attractor — (negative) peace. In the unstable region c), there is a bifurcation to two attractors — peace or war — with oscillation between them. Under certain conditions, further bifurcations can occur, leading to chaos. (One would think that there are only two alternatives in this model, war or peace, and we cannot easily imagine 4, 8…etc. But all that is meant here is that there is no longer a regular (sine wave) oscillation, but alterations unpredictable enough to defy resolution by Fourier analysis.)

Other factors also contribute to the dynamics determining the state of the system. Computer simulations show tendencies to stability when economic considerations predominate (these are presumably more rational and “conservative” in the sense of risk-avoidance). However, when political considerations predominate (one would think of ethnic, religious or ideological factors here), there is divergence to either peace or war, or an oscillation; these factors are presumably more emotional, volatile-impusive, and risk-accepting. Chaotic dynamics tend to result when the oscillations are driven by high motivation for hegemony (i.e. power-seeking behaviours).

Wolfson’s model is attractive because it synthesizes several theories current in peace research. Wars are frequently the result of dynamic processes of competition rather than purposive decisions based on cost-benefit calculations. Myopic rationality, especially if somewhat biased by risk-acceptance, often leads to results not expected or deliberately intended. (Even simple Prisoner’s Dilemma games show this paradox.)

The road chosen at crossroads, though it appears smooth and well-lit at night, may soon lead to impenetrable thickets or treacherous marshes full of crocodiles. What we need is a map for long-range navigation, or maybe help from satellite technology.

What is the social-science analogue of this physical metaphor? A better understanding of the long-range nonlinear dynamics would help; but it must also be supplemented by a reorientation of attitude and decision-making style, at least to long-range rationality if not altruistic universal empathy. More knowledge is necessary, but not sufficient, for wisdom; it must be supplemented by aiming at the long-range sustainability of our political (as well as our ecological) systems.

I append a quote from another Wolfson paper (Journal of Conflict Resolution, March 1992): “The apparent paradox and complexity of conflict trajectories arise as much from the nonlinear nature of the system as from a multiplicity of causes.

Convergent, explosive, oscillating, and chaotic regimes arise from the model, depending on the choice of parameters.”