293 research outputs found
What we regret most . . . and why
Which domains in life produce the greatest potential for regret,
and what features of those life domains explain why? Using
archival and laboratory evidence, the authors show that greater
perceived opportunity within life domains evokes more intense
regret. This pattern is consistent with previous publications demonstrating
greater regret stemming from high rather than low
opportunity or choice. A meta-analysis of 11 regret ranking studies
revealed that the top six biggest regrets in life center on (in
descending order) education, career, romance, parenting, the
self, and leisure. Study Set 2 provided new laboratory evidence
that directly linked the regret ranking to perceived opportunity.
Study Set 3 ruled out an alternative interpretation involving
framing effects. Overall, these findings show that people’s biggest
regrets are a reflection of where in life they see their largest opportunities;
that is, where they see tangible prospects for change,
growth, and renewal
Self-report measures of individual differences in regulatory focus: a cautionary note
Regulatory focus theory distinguishes between two independent structures of strategic inclination,
promotion versus prevention. However, the theory implies two potentially independent definitions
of these inclinations, the self-guide versus the reference-point definitions. Two scales (the
Regulatory Focus Questionnaire [Higgins, E. T., Friedman, R. S., Harlow, R. E., Idson, L. C.,
Ayduk, O. N., & Taylor, A. (2001). Achievement orientations from subjective histories of success:
Promotion pride versus prevention pride. European Journal of Social Psychology, 31, 3–23] and
the General Regulatory Focus Measure [Lockwood, P., Jordan, C. H., & Kunda, Z. (2002). Motivation
by positive and negative role models: Regulatory focus determines who will best inspire us.
Journal of Personality and Social Psychology, 83, 854–864]) have been widely used to measure dispositional
regulatory focus. We suggest that these two scales align respectively with the two definitions,
and find that the two scales are largely uncorrelated. Both conceptual and methodological implications
are discussed
Dare to compare: fact-based versus simulation-based comparison in daily life
We examined the relative frequency of social, counter factual, past-temporal, and future-temporal
comparison in daily life using an experience-sampling method, in which participants were
randomly prompted to record thought samples using palmtop computers carried for two weeks.
Comparative thought accounted for 12% of all thoughts, and all four comparison types occurred
with equivalent frequency. Comparisons may be either fact-based (i.e., based on actuality, as in
social and past-temporal comparison) or simulation-based (i.e., based on imagination, as in
counterfactual and future-temporal comparison). Because the latter are more “unbounded,” and
because greater perceived opportunity invites greater self-improvement, we predicted and found
that counterfactual and future-temporal comparison were more likely to be upward (vs.
downward) than social and past-temporal comparison. All comparison types focused on
approach more than avoidance motives, except for counterfactuals, which showed equivalent
focus on both. These findings reveal the prominence of comparative thought in daily life, and
underscore the value an integrative theory that describes social, counter factual, or temporal
comparison using a common theoretical platform
Praise for regret: people value regret above other negative emotions
What do people think about the emotion of regret? Recent demonstrations of the psychological
benefits of regret have been framed against an assumption that most people find regret to be
aversive, both when experienced but also when recalled later. Two studies explored lay
evaluations of regret experiences, revealing them to be largely favorable rather than unfavorable.
Study 1 demonstrated that regret, but not other negative emotions, was dominated by positive
more than negative evaluations. In both Studies 1 and 2, although participants saw a great deal of
benefit from their negative emotions, regret stood out as particularly beneficial. Indeed, in Study
2, regret was seen to be the most beneficial of 12 negative emotions on all five functions of:
making sense of past experiences, facilitating approach behaviors, facilitating avoidance
behaviors, gaining insights into the self, and in preserving social harmony. Moreover, in Study 2,
individuals made self-serving ascriptions of regret, reporting greater regret experiences for
themselves than for others. In short, people value their regrets substantially more than they do
other negative emotions
Regret and behavior: comment on Zeelenberg and Pieters
Zeelenberg and Pieter's (2007) regret regulation theory 1.0 offers a synthesis that brings
together concepts spanning numerous literatures. We have no substantive disagreement with
their theory, but instead offer
3 observations to further aid regret researchers studying con-
sumer decision making. First, the overall arch of any regret theory must be situated within an
understanding of behavior regulation. Second, the distinction between regrets of action versus
inaction is best understood in terms of motivational implications, particularly with regard to
Higgin's
(1998) distinction between promotion and prevention focus. Third, the opportunity
principle offers a particularly clear means of summarizing the regulatory consequences of the
regret experience. Regret is an emotion pivotal for decision making, and its cognitive under-
pinning has and continues to be elucidated in research focusing on counter factual thinking
"Species traits as predictors of lepidopteran composition in restored and remnant tallgrass prairies"
Keith S. Summerville is a professor of Environmental Science in the Department of Environmental Science and Policy at Drake University. He can be contacted at [email protected] ecologists are increasingly turning to the development of trait-filter models, which predict how evolved traits limit species membership within assemblages depending on existing abiotic or biotic constraints, as a tool to explain how species move from a regional species pool into a restored community. Two often untested assumptions of these models, however, are that species traits can reliably predict species' broadscale distribution and that the effects of traits on community membership do not vary between restored and remnant habitats. The goals of this study were to determine whether combinations of ecological traits predispose moth species toward recolonization of restored prairies and to assess the degree to which restored prairies contain moth assemblages comparable with prairie remnants. In 2004, we collected 259 moth species from 13 tallgrass prairie remnants and restorations in central Iowa. Principal components analysis (PCA) was used to identify significant combinations of ecological traits that were shared by groups of moth species. Logistic regression was then employed to test for significant effects of the trait combinations on the frequency of prairie sites occupied by moth species. PCA partitioned moth traits into four axes that explained a total of 81.6% of the variance. Logistic regression detected significant effects for all four PCA axes on the fraction of sites occupied by moths. Species frequently filtered from the regional species pool into prairies were those that had long flight periods and were multivoltine, displayed a feeding preference for legumes but not other forb families, and were regionally abundant but relatively small in body size. Ordination revealed significant differences in moth communities among prairies, suggesting that species traits and habitat characteristics likely interact to create observed patterns of species recolonization of restorations. Thus, the optimal approach to restoring the lepidopteran fauna of tallgrass prairies may involve locating prairie plantings adjacent to habitat remnants.© 2006 by the Ecological Society of America.The project was supported by the National Research
Initiative of the USDA Cooperative State Research, Education and Extension Service, grant number 2005-35101-15337 as well as from grants from the National Geographic Society, the
National Aeronautic and Space Administration, the Iowa Science Foundation, and Drake University
A Preliminary Checklist of the Moths of Butler County, Ohio
Author Institution: Department of Zoology, Miami UniversityUsing a combination of blacklight, mercury vapor light, and sugar bait sampling techniques, we collected moths over a 2-yr period in Butler County, OH, and compiled a list of 392 species. Seventy-eight percent (305) of these species were found to be new county records. A checklist is provided as a baseline catalogue of the moths of Butler County, OH. An analysis of historical county records revealed a bias towards large or colorful species. Although many species we collected are considered common, several infrequently encountered species were discovered. Our effort suggests that biological surveys in fragmented landscapes may reveal unexpected biological diversity
Tabletop Roleplaying Games as Procedural Content Generators
Tabletop roleplaying games (TTRPGs) and procedural content generators can
both be understood as systems of rules for producing content. In this paper, we
argue that TTRPG design can usefully be viewed as procedural content generator
design. We present several case studies linking key concepts from PCG research
-- including possibility spaces, expressive range analysis, and generative
pipelines -- to key concepts in TTRPG design. We then discuss the implications
of these relationships and suggest directions for future work uniting research
in TTRPGs and PCG.Comment: 9 pages, 2 figures, FDG Workshop on Procedural Content Generation
202
Learning the Designer's Preferences to Drive Evolution
This paper presents the Designer Preference Model, a data-driven solution
that pursues to learn from user generated data in a Quality-Diversity
Mixed-Initiative Co-Creativity (QD MI-CC) tool, with the aims of modelling the
user's design style to better assess the tool's procedurally generated content
with respect to that user's preferences. Through this approach, we aim for
increasing the user's agency over the generated content in a way that neither
stalls the user-tool reciprocal stimuli loop nor fatigues the user with
periodical suggestion handpicking. We describe the details of this novel
solution, as well as its implementation in the MI-CC tool the Evolutionary
Dungeon Designer. We present and discuss our findings out of the initial tests
carried out, spotting the open challenges for this combined line of research
that integrates MI-CC with Procedural Content Generation through Machine
Learning.Comment: 16 pages, Accepted and to appear in proceedings of the 23rd European
Conference on the Applications of Evolutionary and bio-inspired Computation,
EvoApplications 202
Interactive Evolution and Exploration within Latent Level-Design Space of Generative Adversarial Networks
Generative Adversarial Networks (GANs) are an emerging form of indirect
encoding. The GAN is trained to induce a latent space on training data, and a
real-valued evolutionary algorithm can search that latent space. Such Latent
Variable Evolution (LVE) has recently been applied to game levels. However, it
is hard for objective scores to capture level features that are appealing to
players. Therefore, this paper introduces a tool for interactive LVE of
tile-based levels for games. The tool also allows for direct exploration of the
latent dimensions, and allows users to play discovered levels. The tool works
for a variety of GAN models trained for both Super Mario Bros. and The Legend
of Zelda, and is easily generalizable to other games. A user study shows that
both the evolution and latent space exploration features are appreciated, with
a slight preference for direct exploration, but combining these features allows
users to discover even better levels. User feedback also indicates how this
system could eventually grow into a commercial design tool, with the addition
of a few enhancements.Comment: GECCO 202
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