Bounded Rationality and Political Agents Human-Machine Strategic Analysis

Imagine a situation in which a government is sued by a foreign investor under a treaty it signed decades earlier. Before the lawsuit, nobody still in office had ever examined the treaty closely. In one case, a sitting Attorney General had to search “BIT” and “ICSID” online simply to understand what his own government had agreed to (Poulsen & Aisbett, 2013, p. 279). After the lawsuit, however, the same government suddenly began treating every future treaty negotiation as a serious source of legal exposure. Nothing about the underlying risk had changed. What changed was that, for the first time, the risk had become personal, vivid, and impossible to ignore.

In this case, the problem was not that the government calculated incorrectly. The government had not been calculating at all until circumstances forced it to do so. This is the starting point for this essay because it reflects the kind of behaviour that a fully rational, optimising decision maker should not produce, yet that a bounded rational decision maker produces routinely.

Theory

Herbert Simon’s bounded rationality (1957) begins with a simple observation: nobody has the time, information, or computational capacity to identify every possible option in a decision, calculate the full consequences of each one, and then select the true optimum. Real decision makers satisfice. They search until they find an option that clears some internal standard of “good enough,” and then they stop searching rather than continuing until they have proven that it is the best possible choice.

Mintz’s (2007) manifesto for “Behavioural IR” as a subfield gives this insight its clearest modern expression within international relations. His “Six Characteristics of Behavioural IR” (pp. 159-160) are worth stating in full because they effectively form the definitional core of this essay:

1. Leaders often make suboptimal rather than utility maximising decisions.
2. Information processing limits push them toward narrow sets of alternatives and cognitive shortcuts.
3. Biases operate simultaneously at the individual, group, and organisational levels.
4. The discipline should study the decision process, not only the outcome.
5. Rational choice assumes that framing should not matter, yet this assumption is routinely violated.
6. Loss aversion is central to how leaders, groups, and elites actually make choices.

Mintz is explicit that this approach is additive and not a rejection of rational choice IR. “IR research can be viewed as consisting of rational choice and nonrational choice (behavioural) paradigms” (p. 158), with the two operating alongside one another rather than one replacing the other.

Political Mechanism

The clearest demonstration that bounded rationality is a genuine structural feature of political behaviour comes from Ostrom and Marra’s (1986) study of United States Cold War defence budgeting. Political scientists had spent years failing to find evidence that United States defence spending responded to Soviet spending at all, even though successive administrations repeatedly insisted that it did. Reagan told the United Nations in 1982 that spending is “a measure of intentions,” while his own Defence Secretary stated the point even more directly: “it’s the threat that makes the budget.”

Ostrom and Marra found the missing reaction once they modelled the budget process as it actually occurred. Instead of treating the process as one actor solving a single optimisation problem each year, they modelled three organisations, the President, Congress, and the Department of Defence, each applying a simple additive “base plus change” rule to whatever the previous actor in the sequence had just done. Each organisation monitored only a narrow and bounded part of the surrounding environment, and none recalculated the entire budget from first principles during every cycle (pp. 821-824).

Once the process was specified in this way, the model explained the overwhelming majority of the actual increase in defence spending across nearly two decades. It also revealed something more important. Once an inflated estimate of a threat becomes incorporated into an organisation’s baseline, the process contains no mechanism that automatically removes it again, even when the original estimate is later acknowledged to have been wrong (pp. 838-839).

Poulsen and Aisbett’s (2013) study of how developing countries learn from investment treaty lawsuits provides a test of the same mechanism because it was designed to distinguish bounded rational learning from a fully rational Bayesian alternative. These two explanations can often appear identical when viewed only through their outcomes. Across a panel of 138 countries, a country’s first lawsuit under one of its own treaties reduced its future treaty signing rate by roughly one third. However, the cumulative number of later lawsuits against the same country added almost nothing further to this effect (pp. 291-295). Similarly, a lawsuit brought by investors from a particular partner country had no measurable effect on that country’s willingness to sign new treaties with the same partner (pp. 298 to 301).

A Bayesian learner should have updated its beliefs in response to all of this information. A bounded rational learner, relying on Tversky and Kahneman’s availability heuristic, updates primarily in response to events that are vivid and personally experienced while largely ignoring information that is less immediate. The authors describe this pattern, not unfairly, as “narcissistic learning.”

Payne’s (2015) study of United States strategy during the Vietnam War shows the same mechanism operating within individual minds rather than institutions. Robert McNamara’s shift from describing Vietnam as strategically vital to describing Asian trends as “running mostly for, not against, our interests” (p. 156) appears, on the surface, to be a rational response to new evidence. Payne’s argument, however, is that even with extensive documentary access it is empirically impossible to determine whether this reassessment caused McNamara to recognise that the war was being lost, or whether recognising that the war was being lost caused him to reassess its strategic importance (pp. 156-157, 175-176).

This is the same reference point ambiguity that makes bounded rational explanations and rational explanations constructed with hindsight so difficult to distinguish empirically. Goldgeier and Tetlock’s (2001) review places this issue within the broader context of international relations theory. Bounded rationality is not simply a critique attached externally to realism, liberal institutionalism, or constructivism. Each of these paradigms already contains an often unexamined psychological microfoundation, and bounded rationality is simply the one that realist and institutionalist theories have most consistently neglected.

Agent Attributes

An agent designed to satisfice rather than optimise requires a small and specific set of state variables. These variables should deliberately be more limited than those available to a fully rational actor because the purpose of the model is to represent what the agent cannot access, rather than merely describing what it can.

• An information set: partial and local rather than representing the full state of the world.
• An aspiration threshold: the standard an option must meet in order to be accepted, rather than a complete ranking of all possible options.
• A memory base: the previous period’s decision, which is carried forward and adjusted instead of being recalculated from zero. This directly reflects Ostrom and Marra’s “base plus change” logic.
• A bounded environmental monitoring set: a small and fixed list of variables that the agent actually observes while ignoring everything outside that set.
• An availability weighting: the degree to which a recent, vivid, and personally experienced event alters the agent’s perception of current risk relative to the true underlying rate.

Decision Rule

In plain language, an agent scans a limited set of options in a particular order and adopts the first option that clears its aspiration threshold. It does not compare every available option in order to identify the best one. Its perception of current risk is also not equal to the objective base rate. Instead, that perception is pulled toward similar events the agent has personally and recently experienced. The effect is strong when the event directly involves the agent and weak when the same event merely happens to a comparable neighbour.

Interaction and Environment

Two distinct interaction structures appear in the sources discussed above, and a model should choose whichever structure fits the case rather than automatically defaulting to one or the other.

Ostrom and Marra’s budget process is sequential and hierarchical. Each organisational actor responds primarily to the actor immediately upstream from it, while the range of environmental variables being monitored becomes narrower at every stage of the sequence. The President monitors the broadest set of variables, Congress monitors fewer, and the Department of Defence monitors the narrowest set of all (pp. 823-826).

Poulsen and Aisbett’s treaty learning process, by contrast, is networked but asymmetric. A shock experienced directly by an agent produces a sharp behavioural update, while a shock experienced by a network neighbour produces almost no response. Both structures provide legitimate ways of modelling interactions among bounded rational agents, and both differ substantially from the assumption found in many simple diffusion models that information originating anywhere in a population should carry roughly equal weight.

Possible ABM Implementation

A straightforward way to construct this model would be to create a population of agents that choose in each period among protest, repress, cooperate, and escalate while operating with only partial information about the state of their neighbours and their own recent history.

Each agent would carry the five attributes described above. Its aspiration threshold and bounded environmental monitoring set could then be varied experimentally in order to examine how the amount of search an agent performs before satisficing affects outcomes at the system level.

Luteijn’s (2015) generative model of major power war already implements bounded rational state agents along broadly similar lines and therefore provides a useful existing reference point. NetLogo remains the most accessible environment for an initial prototype. A later move to Mesa or a custom framework would become useful once the sequential interaction structure, rather than a flat population, becomes central to the research question.

Observable Emergent Outcomes

Two patterns are particularly worth designing the model to identify because both are counterintuitive and both are directly supported by the sources discussed above rather than merely being theoretically plausible.

The first is path dependence. Because agents satisfice and update from a running base instead of optimising again from the beginning during every period, early and sometimes arbitrary choices can lock the system into an aggregate trajectory that a fully rational population would not have followed. Once established, that trajectory can resist correction even after the information that originally produced it is shown to be wrong. This is exactly what Ostrom and Marra found in the case of the Soviet spending overestimate, which remained embedded in the United States defence baseline rather than being removed once its inaccuracy became clear.

The second pattern follows directly from Poulsen and Aisbett’s dyadic finding. A population of these agents should display almost no diffusion of caution through indirect experience among network neighbours, while simultaneously showing a very strong reaction to shocks that agents experience personally. This produces a clear and falsifiable prediction that a purely Bayesian population of agents would not generate.

Limits

The main difficulty with bounded rationality as a modelling assumption is the problem that Poulsen and Aisbett designed their research to address. In most settings, a bounded rational explanation and a fully rational explanation under imperfect information appear observationally identical from the outside (Meseguer, 2006, discussed at pp. 275, 296 to 301).

Without some structural feature in the data that forces the two explanations apart, as the bilateral and dyad specific structure of investment treaties does in their study, a model claiming to demonstrate bounded rationality may simply be demonstrating rational behaviour under informational conditions that the modeller has not fully specified.

This is the central caution of the essay, and it extends beyond this particular theory. An aspiration threshold, a memory base, or an availability weight inserted into a model without empirical grounding for its specific value does not necessarily perform meaningful behavioural work. Without such grounding, these features risk becoming psychological decoration expressed in the language of a formal model while explaining nothing that a simpler assumption could not explain equally well after the fact.

Model Idea

Agents choose between protest, repress, cooperate, and escalate according to a satisficing threshold applied to partial information that is weighted toward local and personally experienced events. Each period’s position is constructed from the previous period’s base plus a bounded change term rather than through complete optimisation across the entire option set.

Further Reading

• Goldgeier, J. M., & Tetlock, P. E. (2001). Psychology and international relations theory. Annual Review of Political Science, 4(1), 67 to 92.
• Mintz, A. (2007). Why behavioral IR? International Studies Review, 9(1), 157 to 162.
• Ostrom, C. W., Jr., & Marra, R. F. (1986). U.S. defense spending and the Soviet estimate. American Political Science Review, 80(3), 819 to 842.
• Payne, K. (2015). The Psychology of Strategy: Exploring Rationality in the Vietnam War. Oxford University Press.
• Poulsen, L. N. S., & Aisbett, E. (2013). When the claim hits: Bilateral investment treaties and bounded rational learning. World Politics, 65(2), 273 to 313.
• Simon, H. A. (1957). Models of Man: Social and Rational. Wiley.

The next essay in this series takes the same agent and asks what happens when its information is not merely partial but systematically distorted, with availability, representativeness, and anchoring functioning as decision rules in their own right. That comes next: Heuristics and Biases as Agent Rules.