Our hearts go out to all those who may be battling COVID-19. For more information about how COVID-19 might impact the ACSOS 2020 conference, please read the official statement of the Steering Committee and the Organizing Committee.
The SeAC workshop will take place virtually, along with ACSOS 2020, on the original dates (currently this is planned for August, 17, 2020).
We are happy to announce that the SeAC workshop will feature the Keynote about Self-awareness in Online Advertising for Self-managing Campaign Optimization from Dr. Niklas Karlsson (Verizon).
Please mind the extension of the deadline for papers and talk abstracts. Our new deadline is June 19, 2020.
We plan a Special Issue on Self-aware Computing Systems: Applications, Engineering and Evaluation in Elsevier’s Array (https://www.journals.elsevier.com/array): The authors of accepted papers of the SeAC 2020 workshop will be invited to extend their contributions for the publication in this special issue (fees are waived) – more information follows.
During the past decade, many different research communities have explored the aspects of self-awareness in computing systems, each from their own perspective. Relevant work can be found in different areas including autonomic computing, self-adaptive and self-organizing software and systems, machine learning, artificial intelligence and multi-agent systems, organic computing, context- and situation-aware systems, reflective computing, model-predictive control, as well as work from the models@run-time community.
The workshop on self-aware computing (SeAC) provides a forum for the exchange of ideas and experiences in the interdisciplinary area of self-aware computing, fostering interaction and collaborations between the different research communities interested in self-aware computing systems. The workshop was initiated by the 2015 Dagstuhl Seminar 15041 on model-driven algorithms and architectures for self-aware computing systems, which brought together 45 international experts.
As proposed by the seminar and documented in a recent Springer book on the topic, self-aware computing systems are understood in a broad sense seeking to integrate the different ways in which this term is used in the interdisciplinary research landscape.
More specifically, self-aware computing systems are understood as having two main properties. They
»» learn models, capturing knowledge about themselves and their environment (such as their structure, design, state, possible actions, and runtime behavior) on an ongoing basis; and
»» reason using the models (to predict, analyze, consider, or plan), which enables them to act based on their knowledge and reasoning (for example, to explore, explain, report, suggest, self-adapt, or impact their environment)
and do so in accordance with high-level goals, which can change.
The workshop aims to raise awareness about related research efforts in the different communities as well as synergies that can be exploited to advance the state of the art on self-aware computing.