| 1. |
- Brütt, Katharina, et al.
(författare)
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Competition and moral behavior: A meta-analysis of forty-five crowd-sourced experimental designs
- 2023
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Ingår i: Proceedings of the National Academy of Sciences - PNAS. - : National Academy of Sciences. - 1091-6490 .- 0027-8424. ; 120:23
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Tidskriftsartikel (refereegranskat)abstract
- Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity-variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity-estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs-indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.
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| 2. |
- D'Angelo, Mirko, 1989-, et al.
(författare)
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Learning to Learn in Collective Adaptive Systems : Mining Design Patterns for Data-driven Reasoning
- 2020
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Ingår i: IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). - : IEEE. - 9781728184142 ; , s. 121-126
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Konferensbidrag (refereegranskat)abstract
- Engineering collective adaptive systems (CAS) with learning capabilities is a challenging task due to their multidimensional and complex design space. Data-driven approaches for CAS design could introduce new insights enabling system engineers to manage the CAS complexity more cost-effectively at the design-phase. This paper introduces a systematic approach to reason about design choices and patterns of learning-based CAS. Using data from a systematic literature review, reasoning is performed with a novel application of data-driven methodologies such as clustering, multiple correspondence analysis and decision trees. The reasoning based on past experience as well as supporting novel and innovative design choices are demonstrated.
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| 3. |
- D'Angelo, Mirko, et al.
(författare)
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On learning in collective self-adaptive systems : state of practice and a 3D framework
- 2019
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Ingår i: 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). - : IEEE. - 9781728133683 - 9781728133690 ; , s. 13-24
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Konferensbidrag (refereegranskat)abstract
- Collective self-adaptive systems (CSAS) are distributed and interconnected systems composed of multiple agents that can perform complex tasks such as environmental data collection, search and rescue operations, and discovery of natural resources. By providing individual agents with learning capabilities, CSAS can cope with challenges related to distributed sensing and decision-making and operate in uncertain environments. This unique characteristic of CSAS enables the collective to exhibit robust behaviour while achieving system-wide and agent-specific goals. Although learning has been explored in many CSAS applications, selecting suitable learning models and techniques remains a significant challenge that is heavily influenced by expert knowledge. We address this gap by performing a multifaceted analysis of existing CSAS with learning capabilities reported in the literature. Based on this analysis, we introduce a 3D framework that illustrates the learning aspects of CSAS considering the dimensions of autonomy, knowledge access, and behaviour, and facilitates the selection of learning techniques and models. Finally, using example applications from this analysis, we derive open challenges and highlight the need for research on collaborative, resilient and privacy-aware mechanisms for CSAS.
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| 4. |
- Eismann, Simon, et al.
(författare)
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The State of Serverless Applications: Collection, Characterization, and Community Consensus
- 2022
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Ingår i: IEEE Transactions on Software Engineering. - 0098-5589 .- 1939-3520. ; 48:10, s. 4152-4166
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Tidskriftsartikel (refereegranskat)abstract
- Over the last five years, all major cloud platform providers have increased their serverless offerings. Many early adopters report significant benefits for serverless-based over traditional applications, and many companies are considering moving to serverless themselves. However, currently there exist only few, scattered, and sometimes even conflicting reports on when serverless applications are well suited and what the best practices for their implementation are. We address this problem in the present study about the state of serverless applications. We collect descriptions of 89 serverless applications from open-source projects, academic literature, industrial literature, and domain-specific feedback. We analyze 16 characteristics that describe why and when successful adopters are using serverless applications, and how they are building them. We further compare the results of our characterization study to 10 existing, mostly industrial, studies and datasets; this allows us to identify points of consensus across multiple studies, investigate points of disagreement, and overall confirm the validity of our results. The results of this study can help managers to decide if they should adopt serverless technology, engineers to learn about current practices of building serverless applications, and researchers and platform providers to better understand the current landscape of serverless applications.
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