Linear decision rule as aspiration for simple decision heuristics

Research output: Chapter in Book/Report/Conference proceedingChapter

  • 14 Citations

Abstract

Many attempts to understand the success of simple decision heuristics have examined heuristics as an approximation to a linear decision rule. This research has identified three environmental structures that aid heuristics: dominance, cumulative dominance, and noncompensatoriness. Here, we further develop these ideas and examine their empirical relevance in 51 natural environments. We find that all three structures are prevalent, making it possible for some simple rules to reach the accuracy levels of the linear decision rule using less information.
LanguageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States
EditorsC. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, K. Q. Weinberger
PublisherCurran Associates, Inc.
Pages2904-2912
Number of pages9
StatusPublished - 2013

Fingerprint

Aspiration
Decision heuristics
Decision rules
Heuristics
Natural environment
Simple rules
Approximation

Cite this

Şimşek, Ö. (2013). Linear decision rule as aspiration for simple decision heuristics. In C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, & K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States (pp. 2904-2912). Curran Associates, Inc..

Linear decision rule as aspiration for simple decision heuristics. / Şimşek, Özgür.

Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. ed. / C. J. C. Burges; L. Bottou; M. Welling; Z. Ghahramani; K. Q. Weinberger. Curran Associates, Inc., 2013. p. 2904-2912.

Research output: Chapter in Book/Report/Conference proceedingChapter

Şimşek, Ö 2013, Linear decision rule as aspiration for simple decision heuristics. in CJC Burges, L Bottou, M Welling, Z Ghahramani & KQ Weinberger (eds), Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. Curran Associates, Inc., pp. 2904-2912.
Şimşek Ö. Linear decision rule as aspiration for simple decision heuristics. In Burges CJC, Bottou L, Welling M, Ghahramani Z, Weinberger KQ, editors, Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. Curran Associates, Inc.2013. p. 2904-2912.
Şimşek, Özgür. / Linear decision rule as aspiration for simple decision heuristics. Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. editor / C. J. C. Burges ; L. Bottou ; M. Welling ; Z. Ghahramani ; K. Q. Weinberger. Curran Associates, Inc., 2013. pp. 2904-2912
@inbook{557435ddd1d34f81bc83d525783d19c6,
title = "Linear decision rule as aspiration for simple decision heuristics",
abstract = "Many attempts to understand the success of simple decision heuristics have examined heuristics as an approximation to a linear decision rule. This research has identified three environmental structures that aid heuristics: dominance, cumulative dominance, and noncompensatoriness. Here, we further develop these ideas and examine their empirical relevance in 51 natural environments. We find that all three structures are prevalent, making it possible for some simple rules to reach the accuracy levels of the linear decision rule using less information.",
author = "{\"O}zg{\"u}r Şimşek",
year = "2013",
language = "English",
pages = "2904--2912",
editor = "Burges, {C. J. C.} and L. Bottou and M. Welling and Z. Ghahramani and Weinberger, {K. Q.}",
booktitle = "Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States",
publisher = "Curran Associates, Inc.",
address = "USA United States",

}

TY - CHAP

T1 - Linear decision rule as aspiration for simple decision heuristics

AU - Şimşek,Özgür

PY - 2013

Y1 - 2013

N2 - Many attempts to understand the success of simple decision heuristics have examined heuristics as an approximation to a linear decision rule. This research has identified three environmental structures that aid heuristics: dominance, cumulative dominance, and noncompensatoriness. Here, we further develop these ideas and examine their empirical relevance in 51 natural environments. We find that all three structures are prevalent, making it possible for some simple rules to reach the accuracy levels of the linear decision rule using less information.

AB - Many attempts to understand the success of simple decision heuristics have examined heuristics as an approximation to a linear decision rule. This research has identified three environmental structures that aid heuristics: dominance, cumulative dominance, and noncompensatoriness. Here, we further develop these ideas and examine their empirical relevance in 51 natural environments. We find that all three structures are prevalent, making it possible for some simple rules to reach the accuracy levels of the linear decision rule using less information.

UR - http://papers.nips.cc/paper/4888-linear-decision-rule-as-aspiration-for-simple-decision-heuristics

M3 - Chapter

SP - 2904

EP - 2912

BT - Advances in Neural Information Processing Systems 26 (NIPS 2013), 27th Annual Conference on Neural Information Processing Systems 2013: Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States

PB - Curran Associates, Inc.

ER -