1,721,043 research outputs found
Preface
No full textThis book constitutes the revised and selected papers from the 6th International Workshop on Engineering Multi-Agent Systems held in Stockholm, Sweden, in July 2018, in conjunction with AAMAS 2018. The 17 full papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains a state-of-the-art paper that reflects on the role and potential of MAS engineering in a number of key facets. The papers are clustered around the following themes: programming agents and MAS, agent-oriented software engineering, formal analysis techniques, rational agents, modeling and simulation, frameworks and application domains
Engineering Multi-agent Systems Anno 2025
No full textModern software-intensive systems are increasingly blending cyber, physical, and social elements, demanding higher degrees of autonomy and adaptability than ever before. In combination with the ever growing integration and scale of systems, and the inherent uncertainties modern systems face, the principles from MAS engineering remain particularly attractive for engineering systems in a wide variety of domains today. In this chapter, we reflect on the role and potential of MAS engineering on a selection of key facets that characterize modern software engineering practice. We focus at facets that we believe are important in relation to MAS engineering. Concretely, we look at agile development, Cloud and edge computing, distributed ledgers and blockchain, Cyber-Physical Systems and Internet-of-Things, and finally green computing. For each of these facets we highlight opportunities to EMAS engineering, but also the challenges these facets raise. We conclude with highlighting a number of ethical issues that the engineers of modern software-intensive systems and thus also MAS will face in the years to come. © 2019, Springer Nature Switzerland AG.</p
Understanding uncertainty in self-adaptive systems
Full text linkEnsuring that systems achieve their goals under uncertainty is a key driver for self-adaptation. Nevertheless, the concept of uncertainty in self-adaptive systems (SAS) is still insufficiently understood. Although several taxonomies of uncertainty have been proposed, taxonomies alone cannot convey the SAS research community's perception of uncertainty. To explore and to learn from this perception, we conducted a survey focused on the SAS ability to deal with unanticipated change and to model uncertainty, and on the major challenges that limit this ability. In this paper, we analyse the responses provided by the 51 participants in our survey. The insights gained from this analysis include the view - held by 71% of our participants - that SAS can be engineered to cope with unanticipated change, e.g., through evolving their actions, synthesising new actions, or using default actions to deal with such changes. To handle uncertainties that affect SAS models, the participants recommended the use of confidence intervals and probabilities for parametric uncertainty, and the use of multiple models with model averaging or selection for structural uncertainty. Notwithstanding this positive outlook, the provision of assurances for safety-critical SAS continues to pose major challenges according to our respondents. We detail these findings in the paper, in the hope that they will inspire valuable future research on self-adaptive systems
Towards a Prediction of Machine Learning Training Time to Support Continuous Learning Systems Development
No full textThe problem of predicting the training time of machine learning (ML) models has become extremely relevant in the scientific community. Being able to predict a priori the training time of an ML model would enable the automatic selection of the best model both in terms of energy efficiency and in terms of performance in the context of, for instance, MLOps architectures or learning-enabled architectures. In this paper, we present the work we are conducting towards this direction. In particular, we present an extensive empirical study of the Full Parameter Time Complexity (FPTC) approach by Zheng et al., which is, to the best of our knowledge, the only approach formalizing the training time of ML models as a function of both dataset’s and model’s parameters. We study the formulations proposed for the Logistic Regression and Random Forest classifiers, and we highlight the main strengths and weaknesses of the approach. Finally, we observe how, from the conducted study, the prediction of training time is strictly related to the context (i.e., the involved dataset) and how the FPTC approach is not generalizable
Data-Driven Analysis of Gender Fairness in the Software Engineering Academic Landscape
No full textGender bias in education gained considerable relevance in the literature over the years. However, while the problem of gender bias in education has been widely addressed from a student perspective, it is still not fully analysed from an academic point of view. In this work, we study the problem of gender bias in academic promotions (i.e., from Researcher to Associated Professor and from Associated to Full Professor) in the informatics (INF) and software engineering (SE) Italian communities (we restricted to the Italian community since each country has specific and own promotion systems). In particular, we first conduct a literature review to assess how the problem of gender bias in academia has been addressed so far. Next, we describe a process to collect and preprocess the INF and SE data needed to analyse gender bias in Italian academic promotions. Subsequently, we apply a formal bias metric to these data to assess the amount of bias and look at its variation over time. From the conducted analysis, we observe how the SE community presents a higher bias in promotions to Associate Professors and a smaller bias in promotions to Full Professors compared to the overall INF community
A conceptual framework for adaptation
No full textIn this position paper we present a conceptual vision of adap-
tation, a key feature of autonomic systems. We put some stress on the role of control data and argue how some of the programming paradigms and models used for adaptive systems match with our conceptual framework
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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