In this rationale higher decision thresholds make

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Unformatted text preview: nts government intervention and action. In this rationale, higher decision thresholds make government intervention less likely, since more necessary conditions for action are needed than when lower decision thresholds exist. For a given distribution of events, an optimal decision threshold — that would minimize error and/or consequences of error — can be identified. Considering actual outcomes to be the only drivers of government perception of outcomes is consistent with most of the literature on dynamic decision making and dynamic learning in 6 complex systems. In these strands of literature, the perception of outcomes is generally modeled as a delayed understanding of outcomes and, in most cases, as directly related to these outcomes enjoying the benefits of complete and perfect information. This is, in reality, an extremely stringent assumption that we address as we further elaborate our model. Information Cue 1 Information Cue 2 Environment Information Cue 3 Information Cue 4 Government's Judgment of Situation Government's Decision Threshold Government's Action L1 Government's Perception of Outcomes Outcomes Information Cue 5 Figure 4 Government-centric Model In the government-centric model, the construct government’s action is part of one feedback mechanism (Feedback Loop L1 in Figure 4), and so is the outcomes construct. In this model, we propose that government’s action determines the outcomes experienced in the system, which, after a process of identification, become the government’s perception of outcomes. Once the outcomes have been perceived by the government, the government uses this information to update its decision threshold (evaluation of the results of the previous action taken); this threshold, when compared with the government’s judgment of the situation, determines the next set of government actions to be taken. The feedback mechanism described above captures a learning loop in the side of the government, in which the government learns on the basis of the outcomes experienced. The theory of learning used in this part of the model is consistent with reinforcement learning theories (Kolb, 1984) and with outcome-based learning theories (Erev, 1998; Erev, Gopher, Itkin, and Greenshpan, 1995; Hammond,...
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This note was uploaded on 04/05/2010 for the course POL 3232 taught by Professor What during the Spring '10 term at Accreditation Commission for Acupuncture and Oriental Medicine.

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