Posts Tagged: heuristics

Paper: Heuristics for financial regulation

It simply wasn’t true that a world with almost perfect information
was very similar to one in which there was perfect information.
J. E. Stiglitz (2010). Freefall: America, free markets,
and the sinking of the world economy, p. 243

Hansjörg Neth, Björn Meder, Amit Kothiyal, Gerd Gigerenzer

Homo heuristicus in the financial world: From risk management to managing uncertainty

Abstract: What — if anything — can psychology and decision science contribute to risk management in financial institutions? The turmoils of recent economic crises undermine the assumptions of classical economic models and threaten to dethrone Homo oeconomicus, who aims to make decisions by weighing and integrating all available information. But rather than proposing to replace the rational actor model with some notion of biased, fundamentally flawed and irrational agents, we advocate the alternative notion of Homo heuristicus, who uses simple, but ecologically rational strategies to make sound and robust decisions. Based on the conceptual distinction between risky and uncertain environments this paper presents theoretical and empirical evidence that boundedly rational agents prefer simple heuristics over more flexible models. We provide examples of successful heuristics, explain when and why heuristics work well, and illustrate these insights with a fast and frugal decision tree that helps to identify fragile banks.  We conclude that all members of the financial community will benefit from simpler and more transparent products and regulations.

Paper: Competitive mate choice

Hansjörg Neth, Simeon Schächtele, Sulav Duwal, Peter M. Todd

Competitive mate choice: How need for speed beats quests for quality and harmony

Abstract:  The choice of a mate is made complicated by the need to search for partners at the same time others are searching. What decision strategies will outcompete others in a population of searchers? We extend previous approaches using computer simulations to study mate search strategies by allowing direct competition between multiple strategies, evaluating success on multiple criteria. In a mixed social environment of searchers of different types, simple strategies can exploit more demanding strategies in unexpected ways. We find that simple strategies that only aim for speed can beat more selective strategies that aim to maximize the quality or harmony of mated pairs.

Paper: Ranking LOD data with a cognitive heuristic

Arjon Buikstra, Hansjörg Neth, Lael J. Schooler, Annette ten Teije, Frank van Harmelen

Ranking query results from Linked Open Data using a simple cognitive heuristic

Abstract:  We address the problem how to select the correct answers to a query from among the partially incorrect answer sets that result from querying the Web of Data.

Paper: Feedback design for controlling a dynamic multitasking system

If an organism is confronted with the problem of behaving approximately rationally,
or adaptively, in a particular environment, the kinds of simplifications that are suitable
may depend not only on the characteristics—sensory, neural, and other—of the organism,
but equally on the nature of the environment.
H.A. Simon (1956), Rational choice and the structure of the environment, p. 130

[Copyright, 2008]:

Hans Neth, Sunny Khemlani, Wayne Gray (2008)

Feedback design for the control of a dynamic multitasking system: Dissociating outcome feedback from control feedback. Human Factors Journal, 2008.

Hansjörg Neth, Sangeet S. Khemlani, Wayne D. Gray

Feedback design for the control of a dynamic multitasking system: Dissociating outcome feedback from control feedback

Objective: We distinguish outcome feedback from control feedback to show that suboptimal performance in a dynamic multitasking system may be caused by limits inherent to the information provided rather than human resource limits.