Learning from experience and suboptimal rules in decision making

Abstract

Current work in decision-making research has clearly shifted from representing choice processes via normative models (and modifications thereof) to an emphasis on heuristic processes developed within the general framework of cognitive psychology and theories of information processing (Payne, 1980; Russo, 1977; Simon, 1978; Slovic, Fischhoff, & Lichtenstein, 1977; Tversky & Kahneman 1974, 1, 1980). The shift in emphasis from questions about how well people perform to how they perform is certainly important (e.g., Hogarth, 1975). However, the usefulness of studying both questions together is nowhere more evident than in the study of heuristic rules and strategies. The reason for this is that the comparison of heuristic and normative rules allows one to examine discrepancies between actual and optimal behavior, which then raises questions regarding why such discrepancies exist. In this chapter, I focus on how one learns both types of rules from experience. The concern with learning from experience raises a number of issues that have not been adequately addressed; for example, Under what conditions are heuristics learned? How are they tested and maintained in the face of experience? Under what conditions do we fail to learn about the biases and mistakes that can result from their use?