Examining recognition criterion rigidity during testing using a biased-feedback technique: Evidence for adaptive criterion learning

Examining recognition criterion rigidity during testing using a biased-feedback technique: evidence for adaptive criterion learning.

Recognition models often assume that subjects use specific evidence values (decision criteria) to adaptively parse continuous memory evidence into response categories (e.g., "old," "new"). Although explicit pretest instructions influence criterion placement, these criteria appear extremely resistant to change once testing begins. We tested criterion sensitivity to local feedback using a novel b...

A Rigidity Criterion for Non-Convex Polyhedra

Let P be a (non necessarily convex) embedded polyhedron in R, with its vertices on an ellipsoid. Suppose that the interior of P can be decomposed into convex polytopes without adding any vertex. Then P is infinitesimally rigid. More generally, let P be a polyhedron bounding a domain which is the union of polytopes C1, · · · , Cn with disjoint interiors, whose vertices are the vertices of P . Su...

An Adaptive Regularization Criterion for Supervised Learning

Social influences on adaptive criterion learning.

People adaptively shift decision criteria when given biased feedback encouraging specific types of errors. Given that work on this topic has been conducted in nonsocial contexts, we extended the literature by examining adaptive criterion learning in both social and nonsocial contexts. Specifically, we compared potential differences in criterion shifting given performance feedback from social so...

Age Effects in Adaptive Criterion Learning.

OBJECTIVE Although prior work has examined age-related changes to criterion placement and flexibility, no study tested these constructs through a paradigm that employs adaptive feedback to encourage specific criterion changes. The goal of this study was to assess age differences in how young and older adults adapt and shift criteria in recognition memory decisions based on trial-by-trial feedba...