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This title is part of UC Press's Voices Revived program, which commemorates University of California Press's mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1985

AbstractCharles Lindblom's 1959 essay "The Science of 'Muddling Through'" is best known for the strategy of decision making—disjointed incrementalism—that it recommended. That famous paper and Lindblom's related work also provided two theories: a critique of the conventional method (the synoptic approach) and an argument for using incrementalism instead. Both are applied theories: they are designed to help solve complex policy problems. Lindblom's negative applied theory has stood the test of time well: the empirical foundations of its main micro‐component (cognitive constraints of individuals) and its central macro‐component (the impact of preference conflict on policy making) have grown stronger since 1959. The picture regarding the positive applied theory is more mixed. As a coherent decision‐making strategy, disjointed incrementalism has almost disappeared. Yet its key elements, the major heuristics identified in "Muddling Through," are thriving in many applied fields. Intriguingly, they are often accompanied by subroutines—especially optimization as a choice rule—typically associated with the synoptic approach.

▪ Abstract  Although Herbert Simon's work is often cited by political scientists, it has not generated a large research program in the discipline. This is a waste of a major intellectual resource. The main challenge to the rational choice research program—now the most important research program in political science—can be developed by building on Simon's ideas on bounded rationality. The essay defends this assertion by examining how the work of both the early Simon (primarily satisficing-and-search models) and the later Simon (on problem solving) can shed light on important topics in our discipline such as budgeting, turnout, and party competition.

As arguments about the effectiveness of "muddling through" have proven frustratingly inconclusive, incrementalism—once a major approach to the study of boundedly rational policy processes—has gone dormant. In an attempt to revitalize the debate, I present a formal model of muddling through. The model, by clarifying the logical structure of the informal theory, presents a clearer target for criticism. More importantly, it establishes numerous deductive results. First, some of Lindblom's less controversial conjectures—about the benefits of seriality (repeated attacks on the same policy problem) and redundancy (multiple decision makers working on the same problem)—turn out to be correct if conflict across policy domains is absent or takes certain specified forms. But given other empirically reasonable types of conflict, even these claims are wrong. Second, the advantages of incremental (local) policy search (Lindblom's best-known and most controversial claim) turn out to be still less well founded: in many empirically plausible contexts the claim is invalid.

It is well known that inferential errors can induce nice but provocable strategies to engage in vendettas with each other. It is therefore generally believed that imperfect monitoring reduces the payoffs of such strategies and impairs the evolution of cooperation. The current literature, however, only scrutinizes specific strategies, either analytically or in particular tournaments. This article examines in a more general way how monitoring uncertainty affects the fate of cooperation in tournaments of the iterated prisoner's dilemma (IPD). The first set of results shows that imperfect monitoring does create a sharp trade-off between cooperativeness and unexploitability. The second set examines how random shocks affect the tournament payoffs of several large classes of strategies in the IPD, and shows how noise can help certain nice strategies. The third set analyzes how imperfect monitoring can facilitate the emergence of cooperation based on a population of non-nice strategies. Thus the idea that inferential uncertainty always harms nice strategies and always impairs the evolution of cooperation must be sharply qualified.

Formal analysis is fairly new in public administration, and there is some scepticism in the field about the intellectual advantages of mathematical methods. This is appropriate. Using these methods is now faddish, and fads can cause goal displacement. A formal model of bureaucracy should be only a tool for deepening our knowledge about public organizations. If the underlying ideas are silly, translating them into mathematics will do little good. If they are promising, however, deductive reasoning can help us explore their potential: if one believesAis a general property of bureaucracies, to fail to work outA's logical implications would be throwing away information. Analysis can also increase the falsifiability of our ideas: ifAimpliesBbut empirically we find not-B, the truth status ofAis brought into question. Or it may turn out, as Arrow discovered about democratic principles, that our informal ideas are logically inconsistent: we thought propertiesCandDdescribe existing or possible institutions, but recasting the ideas into mathematical form reveals that such an institution is impossible. Finally, some problems are just too hard to tackle without formal tools. It is unlikely, for example, that Robert Axelrod would have discovered the robustness of the simple strategy of tit-for-tat in the two person prisoners' dilemma without the help of a computer (to pit tit-for-tat against many opponents in thousands of rounds of play) and of mathematics (to prove some generic properties of tit-for-tat).