Formulates and presents a satisficing decision paradigm, using a cost benefit tradeoff, and generates a decision rule applicable to both designing intelligent machines and describing human behavior. In the debate between simple inference heuristics and complex decision mechanisms, the authors suggest that a decision making process that extends to both naturalistic and novel settings should extend beyond the confines of this debate. Both simple heuristics and complex mechanisms are cognitive skills adapted to and appropriate for some circumstances but not for others. Rather than ask which skill is better, it may be more important to ask when a skill is justified. The selection and application of an appropriate cognitive skill for a particular problem has costs and benefits, and therefore requires the resolution of a tradeoff. In revisiting satisficing, it is suggested that the essence of satisficing is tradeoff. Unlike heuristics, which derive their justification from empirical phenomena, and unlike optimal solutions, which derive their justification by an evaluation of alternatives, satisficing decision-making derives its justification by an evaluation of consequences.
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