2013, Morais, Ana Sofia, Neth, Hansjörg, Hills, Thomas

We model the semantic recall sequences of 424 older adults aged between 69 to 103 years in the animal fluency task. Our results suggest that, under normal intellectual functioning, memory search in old age (69–84 years) is consistent with a dynamic process that switches between retrieval probes. With dementia and very old age (85–103 years), however, memory search seems to become more consistent with a static process that activates items in memory as a function of their frequency. The weight that probes have in determining the activation of items in memory seems to be an informative signature of the impact of healthy aging and dementia on memory search. Our results show that, with healthy aging and dementia, the activation of items in memory is increasingly more determined by the frequency of past experience with those items.

2011, Buikstra, Arjon, Neth, Hansjörg, Schooler, Lael, Teije, Annette ten, Harmelen, Frank van

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.

Our hypothesis is that cognitively inspired similarity measures can be exploited to filter the correct answers from the full set of answers. These measure are extremely simple and efficient when compared to those proposed in the literature, while still producing good results.

We validate this hypothesis by comparing the performance of our heuristic to human-level performance on a benchmark of queries to Linked Open Data resources. In our experiment, the cognitively inspired similarity heuristic scored within 10% of human performance. This is surprising given the fact that our heuristic is extremely simple and efficient when compared to those proposed in the literature.

A secondary contribution of this work is a freely available benchmark of 47 queries (in both natural language and SPARQL) plus gold standard human answers for each of these and 1896 SPARQL answers that are human-ranked for their quality.

2013, Neth, Hansjörg, Czienskowski, Uwe, Schooler, Lael J., Gluck, Kevin

Fast and Frugal Trees (FFTs) are a quintessential family of simple heuristics that allow effective and efficient binary clas- sification decisions and often perform remarkably well when compared to more complex methods. This half-day tutorial will familiarize participants with examples of FFTs and elu- cidate the theoretical link between FFTs and signal detection theory (SDT). A range of presentations, practical exercises and interactive tools will enable participants to construct and eval- uate FFTs for different data sets.

2011, Neth, Hansjörg, Schächtele, Simeon, Duwal, Sulav, Todd, Peter M.

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.

2011, Neth, Hansjörg, Payne, Stephen J.

Does using our hands help us to add the value of a set of coins? We test the benefits and costs of direct interaction with a men- tal arithmetic task in a computerized yoked design in which groups of participants vary in their interactive mode (move vs. look) and the initial configuration of coins (pseudo-random vs. another mover’s final layout). By assessing performance and conducting a microgenetic analysis of the strategies employed we argue that the purpose of movement is the result, rather than the process of moving. Participants move coins in order to sort, rather than to mark, and select them by value, rather than by location. They spontaneously create remarkably smart solutions, thereby incidentally creating physical configurations that can help other problem solvers.