Formal studies of decision threshold learning assume full feedback conditions, that is, no matter what the decision is (positive or negative), the decision maker will be provided by feedback. However, in the real world feedback may be conditional on the decision made. In this paper, we investigate how conditional feedback can result in biased decisions. First, based on signal detection theory, a dynamic model of threshold learning is proposed. Then, the model is adjusted to examine effects of conditional feedback on learning and decision making. Then, the model is used to replicate some empirical findings. The results suggest conditional feedback can be a barrier to learning. Further, this study warns about problems of the current assumption of full feedback condition in most dynamic decision-making studies.

This is the whole item.

Date created

• 2008 July 20-2008 July 24

Type

• Document

Processing Activity

• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

License

• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
  Contact Us for questions or additional rights.

ITEM CONTEXT

Part of

6cbae5a21467df4434abbc87da443217

Scope and Contents

Part of

ce498623f0349395d0a141a0525190a0

Scope and Contents

Part of

23d738ba88f8333bc39725f9cb5bd0b8

Scope and Contents

Collection

System Dynamic Society Records

Scope and Contents

Collecting area

• This collection is part of the University Archives