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Measures such as conditional value-at-risk (CVaR) precisely characterize the influence that rare, catastrophic, events can exert over decisions. CVaR compounds in complex ways over sequences of decisions -- by averaging out or multiplying -- formalized in recent work [1] as three structurally different approaches. Existing cognitive tasks fail to discriminate these approaches well; here, we provide examples that highlight their unique characteristics, and make formal links to temporal discounting for the two of the approaches that are time-consistent. These examples can serve as a basis for future experiments with the broader aim of characterizing (potentially maladaptive) risk attitudes in psychopathological populations.
Author Information
Christopher Gagne (Max Planck Institute, Biological Cybernetics)
Peter Dayan (Max Planck Institute for Biological Cybernetics)
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