Posts in Category: conference

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: Immediate interactive behavior (IIB)


immediate behavior, responses that must be made to some stimulus
within very approximately one second (that is, roughly from ~300 ms to ~3 sec). (…)
… immediate behavior is where the architecture shows through — where you can see
the cognitive wheels turn and hear the cognitive gears grind.  Immediate behavior is
the appropriate arena in which to discover the nature of the cognitive architecture.
A. Newell (1990), Unified theories of cognition, p. 235f.

[Copyright neth.de, 2007]:

Hans Neth, Rich Carlson, Wayne Gray, Alex Kirlik, David Kirsh, and Steve Payne (2007): Immediate interactive behavior: How embodied and embedded cognition uses and changes the world to achieve its goals. Symposium held at CogSci 2007.

Hansjörg Neth, Richard A. Carlson, Wayne D. Gray, Alex Kirlik, David Kirsh, Stephen J. Payne

Immediate interactive behavior: How embodied and embedded cognition uses and changes the world to achieve its goals

Summary:  We rarely solve problems in our head alone. Instead, most real-world problem solving and routine behavior recruits external resources and achieves its goals through an intricate process of interaction with the physical environment.  Immediate interactive behavior (IIB) entails all adaptive activities of agents that routinely and dynamically use their embodied and environmentally embedded nature to augment cognitive processes. IIB also characterizes an emerging domain of cognitive science research that studies how cognitive agents exploit and alter their task-environments in real-time. Examples of IIB include arranging coins when adding their values, solving a problem with paper and pencil, arranging tools and ingredients while preparing a meal, programming a VCR, and flying an airplane.

Paper: Juggling multiple tasks in a synthetic task environment


Doing two things at once, like singing while you take a shower,
is not the same as instant messaging while writing a research report.
Don’t fool yourself into thinking you can multitask jobs that need your
full attention. You’re not really having a conversation while you write;
you’re shifting your attention back and forth between the two activities quickly.
You’re juggling. When you juggle tasks, your work suffers AND takes longer
— because switching tasks costs.
Gina Trapani, Work Smart, FastCompany.com

[Copyright neth.de, 2006]:

Hans Neth, Brittney Oppermann, Sunny Khemlani, Wayne Gray (2006)

Juggling multiple tasks: A rational analysis of multitasking in a synthetic task environment.

Paper presented at HFES 2006, San Francisco, CA, USA.

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

Juggling multiple tasks: A rational analysis of multitasking in a synthetic task environment

Abstract:  Tardast (Shakeri 2003; Shakeri & Funk, in press) is a new and intriguing paradigm to investigate human multitasking behavior, complex system management, and supervisory control.  We present a replication and extension of the original Tardast study that assesses operators’ learning curve and explains gains in performance in terms of increased sensitivity to task parameters and a superior ability of better operators to prioritize tasks.  We then compare human performance profiles to various artificial software agents that provide benchmarks of optimal and baseline performance and illustrate the outcomes of simple heuristic strategies.  Whereas it is not surprising that human operators fail to achieve an ideal criterion of performance, we demonstrate that humans also fall short of a principally achievable standard.  Despite significant improvements with practice, Tardast operators exhibit stable sub-optimal performance in their time-to-task allocations.

Paper: Melioration despite informative feedback

In many ways the word ‘meliorizing’ expresses a sensible middle way between optimizing and satisficing.  Where optimus means best, melior means better. (…)
Like a river, natural selection blindly meliorizes its way down successive lines of immediately available least resistance. The animal that results is not the most perfect design conceivable, nor is it merely good enough to scrape by.  It is the product of a historical sequence of changes, each one of which represented, at best, the better of the alternatives that happened to be around at the time.
Richard Dawkins (1982), The Extended Phenotype: The Long Reach of the Gene, p. 46

[Copyright neth.de, 2005–2014]:

Hans Neth, Chris Sims, Wayne Gray (2005).

Melioration despite more information: The role of feedback frequency in stable suboptimal performance.

Paper presented at HFES 2005.

Hansjörg Neth, Chris R. Sims, Wayne D. Gray

Melioration despite more information: The role of feedback frequency in stable suboptimal performance

Abstract:  Situations that present individuals with a conflict between local and global gains often result in a behavioral pattern known as melioration — a preference for immediate rewards over higher long-term gains.  Using a variant of a paradigm by Tunney & Shanks (2002), we explored the potential role of feedback as a means to reduce this bias.  We hypothesized that frequent and informative feedback about optimal performance might be the key to enable people to overcome the documented tendency to meliorate when choices are rewarded probabilistically.  Much to our surprise, this intuition turned out to be mistaken. Instead of maximizing, 19 out of 22 participants demonstrated a clear bias towards melioration, regardless of feedback condition.  From a human factors perspective, our results suggest that even frequent normative feedback may be insufficient to overcome inefficient choice allocation. We discuss implications for the theoretical notion of rationality and provide suggestions for future research that might promote melioration as an explanatory mechanism in applied contexts.