Initial Crisis Reaction and Poliheuristic Theory

Abstract

Poliheuristic (PH) theory models foreign policy decisions using a two-stage process. The first step eliminates alternatives on the basis of a simplifying heuristic. The second step involves a selection from among the remaining alternatives and can employ a more rational and compensatory means of processing information. The PH model posits that strategic/realist factors are more important in the second step of the process. The model is tested for the years 1918 to 1994, using crisis actors from the International Crisis Behavior data set. Results show that domestic political loss has a negative impact on the use of violence in response to a crisis trigger. Contiguity, joint democracy, and trigger are also significant in the expected directions. Relative capabilities have a positive impact, and enduring rivals do not appear more likely to use violence against each other as a first response in a crisis.A key divergence in the empirical study of international relations has been that between cognitive and systemic/rational approaches (Hagan 2001). All too often, each school has considered the other as overly deterministic or ad hoc. Jerel Rosati (2001) takes this discussion a step further because he calls for a merger between rational and cognitive approaches. Like Hagan (2001), Rosati asserts that scholars should not treat the state as a "black box." In other words, we need to explore state actions as a function of the human cognition of their leaders. By dismissing the human cognition component of decisions, we may be discarding important information. Focusing on the rational model alone might give only information about outcomes and preferences. Looking at cognitive issues can tell us about processes and beliefs as well as where preferences come from and how they are established. Rosati suggests that the

An AHP-QFD approach to developing DSS for crisis management

“…Several techniques and tools are available to support decision-analysts in synthesising the fragments of information, gleaning the most possible from their content, and forming a base of knowledge for decision making (DeRouen and Sprecher, 2004). Knowledge in crisis management context includes domain-specific rules, heuristics, boundaries, constraints, previous outcomes, know-how, and entities behaviour (Fischer and Mastaglio, 1991;Nevo and Chan, 2007).…”

Simulating closed regimes with agent based models

“…To begin with, they have preferences [0,10] and salience weights [0,1] on each of a set of M policy issues, which are specified at the start of a run to reflect the regime configuration of interest. An agent may also derive power from a formal position (r_power).…”

“…In our view, this alternative makes sense because these regimes have the hallmarks of CAS, which include (a) heterogeneous agents, (b) interacting with each other and their environment in nonrandom ways, (c) often using non-linear rules to decide what actions to take, (d) both creating and responding to positive and negative feedback processes, and (e) sometimes adapting and learning to achieve better results over time. Various types of computer simulations permit one to capture these features and to explore their association with the dynamic properties of the system.For purposes of studying closed regimes, we develop an exploratory agent-based model [1][2][3], employing a hybrid of the landscape metaphor [3][4][5] and the rule-based systems approach [6], while also building upon prior work concerning coalition formation [7], heuristic-driven decision-making [8][9][10][11][12][13], the cognitive dispositions of leaders [14][15][16], and expected utility [17][18][19]. Sections 2-4 outline the foundations and components of the model.…”

“…For ease of visual representation, we consider models where M 5 2. Thus, the x and y dimensions correspond to two issues, each with a range of policy options [0,10]. The exact nature of these issues is not critical, though logically they should not be entirely collinear, so an agent can exhibit contrasting preferences.…”

“…For purposes of studying closed regimes, we develop an exploratory agent-based model [1][2][3], employing a hybrid of the landscape metaphor [3][4][5] and the rule-based systems approach [6], while also building upon prior work concerning coalition formation [7], heuristic-driven decision-making [8][9][10][11][12][13], the cognitive dispositions of leaders [14][15][16], and expected utility [17][18][19]. Sections 2-4 outline the foundations and components of the model.…”