27 citations · 46 across the 12 of their papers we have counts for
12 papers
Self-Explainability in Self-Adaptive and Self-Organising Systems: Status and Research Directions
Tom Beyer, Svea Wisy, Sven Tomforde
The growing complexity of self-adaptive and self-organising systems, fuelled by advances in Artificial Intelligence (AI), has made them increasingly difficult to understand and tru…
BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics
Lukas Rauch, Raphael Schwinger, Moritz Wirth +8
Deep learning (DL) has greatly advanced audio classification, yet the field is limited by the scarcity of large-scale benchmark datasets that have propelled progress in other domai…
Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers
Lukas Rauch, Raphael Schwinger, Moritz Wirth +3
We propose a shift towards end-to-end learning in bird sound monitoring by combining self-supervised (SSL) and deep active learning (DAL). Leveraging transformer models, we aim to…
Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents
Malte Lehna, Jan Viebahn, Christoph Scholz +2
The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production. As a consequence, active grid manage…
A Quantification Approach for Transferability in Lifelike Computing Systems
Martin Goller, Sven Tomforde
The basic idea of lifelike computing systems is the transfer of concepts in living systems to technical use that goes even beyond existing concepts of self-adaptation and self-orga…
Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptation
Simon Reichhuber, Sven Tomforde
Intelligent systems have the ability to improve their behaviour over time taking observations, experiences or explicit feedback into account. Traditional approaches separate the le…
Towards Organic Distribution Systems -- The Vision of Self-Configuring, Self-Organising, Self-Healing, and Self-Optimising Power Distribution Management
Inga Loeser, Martin Braun, Christian Gruhl +3
Due to the decarbonisation of energy use, the power system is expected to become the backbone of all energy sectors and thus the basic critical infrastructure. High penetration wit…
Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning
Mirko D'Angelo, Sona Ghahremani, Simos Gerasimou +4
Engineering collective adaptive systems (CAS) with learning capabilities is a challenging task due to their multi-dimensional and complex design space. Data-driven approaches for C…
Collaborative Interactive Learning -- A clarification of terms and a differentiation from other research fields
Tom Hanika, Marek Herde, Jochen Kuhn +8
The field of collaborative interactive learning (CIL) aims at developing and investigating the technological foundations for a new generation of smart systems that support humans i…
On the Detection of Mutual Influences and Their Consideration in Reinforcement Learning Processes
Stefan Rudolph, Sven Tomforde, Jörg Hähner
Self-adaptation has been proposed as a mechanism to counter complexity in control problems of technical systems. A major driver behind self-adaptation is the idea to transfer tradi…
Self-Adaptation of Activity Recognition Systems to New Sensors
David Bannach, Martin Jänicke, Vitor F. Rey +3
Traditional activity recognition systems work on the basis of training, taking a fixed set of sensors into account. In this article, we focus on the question how pattern recognitio…
Organic Computing in the Spotlight
Sven Tomforde, Bernhard Sick, Christian Müller-Schloer
Organic Computing is an initiative in the field of systems engineering that proposed to make use of concepts such as self-adaptation and self-organisation to increase the robustnes…