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ORCIDSven Tomforde
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- affiliation: University of Hanover, Germany
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2020 – today
- 2024
[j24]Nikita Smirnov
, Sven Tomforde:
Real-time rate control of WebRTC video streams in 5G networks: Improving quality of experience with Deep Reinforcement Learning. J. Syst. Archit. 148: 103066 (2024)- [c142]Ghassan Al-Falouji, Tom Beyer, Shang Gao, Sven Tomforde:
Steering Towards Maritime Safety with True Motion Predictions Ensemble. ACSOS-C 2024: 7-12 - [c141]Danilo Pianini, Sven Tomforde:
Towards Adaptive Trajectories for Mixed Autonomous and Human-Operated Ships. ACSOS-C 2024: 29-34 - [c140]Pia Schweizer, Jonas Lange, Elia Henrichs, Sven Tomforde, Christian Krupitzer:
Towards a Hybrid Architecture for Self-Adaptive and Self-Organizing Systems. ACSOS-C 2024: 41-46 - [c139]Ghassan Al-Falouji, Shang Gao, Lukas Haschke, Dirk Nowotka, Sven Tomforde:
Enhancing Maritime Behaviour Analysis Through Novel Feature Engineering and Digital Shadow Modelling: A Case Study in the Kiel Fjord. ARCS 2024: 97-111 - [c138]Connor Schönberner, Sven Tomforde:
XCS: Is Covering All You Need? GECCO Companion 2024: 1788-1796 - [c137]Michel Spils, Sven Tomforde:
An Optimised Ensemble Approach for Multivariate Multi-Step Forecasts Using the Example of Flood Levels. ICAART (2) 2024: 388-396 - [c136]Jakob Nazarenus, Simon Reichhuber, Manuel Amersdorfer, Lukas Elsner, Reinhard Koch, Sven Tomforde, Hossam Abbas:
Learning Occlusions in Robotic Systems: How to Prevent Robots from Hiding Themselves. ICAART (2) 2024: 482-492 - [c135]Md Faisal Kabir, Sven Tomforde:
A Deep Analysis for Medical Emergency Missing Value Imputation. ICAART (3) 2024: 1229-1236 - [c134]Nikita Smirnov, Sven Tomforde:
Gymir5G: A Simulation Platform to Study Data Transmission over WebRTC in 5G Networks with Deep Learning Assistance. SoftCOM 2024: 1-6 - [i17]Lukas Rauch, Raphael Schwinger, Moritz Wirth, René Heinrich, Jonas Lange, Stefan Kahl, Bernhard Sick, Sven Tomforde, Christoph Scholz:
BirdSet: A Multi-Task Benchmark for Classification in Avian Bioacoustics. CoRR abs/2403.10380 (2024) - [i16]Nikita Smirnov, Sven Tomforde:
Exploring the Dynamics of Data Transmission in 5G Networks: A Conceptual Analysis. CoRR abs/2404.16508 (2024) - [i15]Malte Lehna, Clara Holzhüter, Sven Tomforde, Christoph Scholz:
HUGO - Highlighting Unseen Grid Options: Combining Deep Reinforcement Learning with a Heuristic Target Topology Approach. CoRR abs/2405.00629 (2024) - [i14]Malte Lehna, Mohamed Hassouna, Dmitry Degtyar, Sven Tomforde, Christoph Scholz:
Fault Detection for agents on power grid topology optimization: A Comprehensive analysis. CoRR abs/2406.16426 (2024) - [i13]Danilo Pianini, Sven Tomforde:
Towards adaptive trajectories for mixed autonomous and human-operated ships. CoRR abs/2409.12714 (2024) - [i12]Fatahlla Moreh, Yusuf Hasan, Bilal Zahid Hussain, Mohammad Ammar, Sven Tomforde:
MicroCrackAttentionNeXt: Advancing Microcrack Detection in Wave Field Analysis Using Deep Neural Networks through Feature Visualization. CoRR abs/2411.10015 (2024) - [i11]Fatahlla Moreh, Yusuf Hasan, Bilal Zahid Hussain, Mohammad Ammar, Sven Tomforde:
Deep Learning for Micro-Scale Crack Detection on Imbalanced Datasets Using Key Point Localization. CoRR abs/2411.10389 (2024) - 2023
- [j23]Anthony Stein, Sven Tomforde, Jean Botev, Peter R. Lewis:
Special Issue on Lifelike Computing Systems. Artif. Life 29(4): 390-393 (2023) - [j22]Konstantin Piliuk, Sven Tomforde:
Artificial intelligence in emergency medicine. A systematic literature review. Int. J. Medical Informatics 180: 105274 (2023) - [c133]Martin Goller, Ingo Thomsen, Ghassan Al-Falouji, Sven Tomforde:
Abnormal Behaviour Detection of Self-Adaptive Agents in Traffic Environments. ACSOS-C 2023: 41-46 - [c132]Ghassan Al-Falouji, Tom Beyer, Sven Tomforde:
From Social Robots to Autonomous Surface Vessels' Navigation. ACSOS-C 2023: 59-64 - [c131]Ghassan Al-Falouji, Lukas Haschke, Dirk Nowotka, Sven Tomforde:
Self-Explanation as a Basis for Self-Integration - The Autonomous Passenger Ferry Scenario. ACSOS-C 2023: 65-70 - [c130]Nikita Smirnov, Sven Tomforde:
Real-Time Data Transmission Optimization on 5G Remote-Controlled Units Using Deep Reinforcement Learning. ARCS 2023: 281-295 - [c129]Raphael Schwinger, Ghassan Al-Falouji, Sven Tomforde:
Autonomous Ship Collision Avoidance Trained on Observational Data. ARCS 2023: 296-310 - [c128]Simon Reichhuber, Sven Tomforde:
Exotic Bets: Evolutionary Computing Coupled with Bet Mechanisms for Model Selection. ICAART (2) 2023: 259-267 - [c127]Tobias Weiss, Simon Reichhuber, Sven Tomforde:
From Simulated to Real Environments: Q-Learning for MAZE-Navigation of a TurtleBot. ICAISC (2) 2023: 192-203 - [c126]Sven Tomforde, Yanneck Ohl, Ingo Thomsen:
Incident-Aware Distributed Signal Systems in Self-Organised Traffic Control Systems. VEHITS 2023: 15-26 - [c125]Ingo Thomsen, Torben Brennecke, Sven Tomforde:
Distributed Collaborative Incident Validation in a Self-Organised Traffic Control System. VEHITS 2023: 152-159 - [c124]Sören Striewski, Ingo Thomsen, Sven Tomforde:
Approaches to Automatic Road Traffic Incident Detection and Incident Forecasting. VEHITS 2023: 289-296 - [e6]Georgios I. Goumas, Sven Tomforde, Jürgen Brehm, Stefan Wildermann, Thilo Pionteck:
Architecture of Computing Systems - 36th International Conference, ARCS 2023, Athens, Greece, June 13-15, 2023, Proceedings. Lecture Notes in Computer Science 13949, Springer 2023, ISBN 978-3-031-42784-8 [contents] - [e5]Anthony Stein, Sven Tomforde, Jean Botev, Peter R. Lewis:
Proceedings of the LIFELIKE 2022 - 10th Edition in the Evolution of the Workshop Series of Autonomously Learning and Optimizing Systems (SAOS) co-located with 2022 Conference on Artificial Life (ALIFE 2022), Online, July 20th, 2022. CEUR Workshop Proceedings 3461, CEUR-WS.org 2023 [contents] - [i10]Martin Goller, Sven Tomforde:
A Quantification Approach for Transferability in Lifelike Computing Systems. CoRR abs/2301.12854 (2023) - [i9]Malte Lehna, Jan Viebahn, Christoph Scholz, Antoine Marot, Sven Tomforde:
Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents. CoRR abs/2304.00765 (2023) - [i8]Lukas Rauch, Raphael Schwinger, Moritz Wirth, Bernhard Sick, Sven Tomforde, Christoph Scholz:
Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers. CoRR abs/2308.07121 (2023) - 2022
- [j21]Christian Krupitzer, Christian Gruhl, Bernhard Sick, Sven Tomforde:
Proactive hybrid learning and optimisation in self-adaptive systems: The swarm-fleet infrastructure scenario. Inf. Softw. Technol. 145: 106826 (2022) - [j20]Sören Christensen, Sven Tomforde:
Reinforcement learning as a basis for cross domain fusion of heterogeneous data. Inform. Spektrum 45(4): 214-217 (2022) - [j19]Sören Christensen, Sven Tomforde:
Reinforcement learning as a basis for cross domain fusion of heterogeneous data. Inform. Spektrum 45(5): 295-299 (2022) - [c123]Martin Goller, Sven Tomforde:
Identifying Adaptation Changes in Collections of Self-Adaptive Systems. ACSOS-C 2022: 101-106 - [c122]Ghassan Al-Falouji, Christian Gruhl, Torben Neumann, Sven Tomforde:
A Heuristic for an Online Applicability of Anomaly Detection Techniques. ACSOS-C 2022: 107-112 - [c121]Christian Gruhl, Sven Tomforde, Bernhard Sick:
Self-Aware Microsystems. ACSOS-C 2022: 126-127 - [c120]Connor Schönberner, Sven Tomforde:
Deep Reinforcement Learning with a Classifier System - First Steps. ARCS 2022: 256-270 - [c119]Nikita Smirnov, Sven Tomforde:
Navigation Support for an Autonomous Ferry Using Deep Reinforcement Learning in Simulated Maritime Environments. CogSIMA 2022: 142-149 - [c118]Michael Meyer, Marc Unzueta, Georg Kuschk, Sven Tomforde:
Ego-Motion Compensation of Range-Beam-Doppler Radar Data for Object Detection. ECCV Workshops (1) 2022: 697-708 - [c117]Simon Reichhuber, Sven Tomforde:
Evolving Gaussian Mixture Models for Classification. ICAART (3) 2022: 964-974 - [c116]Martin Goller, Sven Tomforde:
Runtime Assessment of the Parameter Utilisation in Adaptive Systems. PerCom Workshops 2022: 200-205 - [c115]Sven Tomforde, Ingo Thomsen:
A Concept for Collaborative Incident Validation in a Self-organised Traffic Management System. VEHITS 2022: 316-323 - [c114]Ingo Thomsen, Sven Tomforde:
Intersection-centric Urban Traffic Flow Clustering for Incident Detection in Organic Traffic Control. VEHITS 2022: 410-417 - [i7]Simon Reichhuber, Sven Tomforde:
Active Reinforcement Learning - A Roadmap Towards Curious Classifier Systems for Self-Adaptation. CoRR abs/2201.03947 (2022) - 2021
- [j18]Martin Goller, Sven Tomforde:
On the stability of (self-)adaptive behaviour in continuously changing environments: A quantification approach. Array 11: 100069 (2021) - [j17]Christian Gruhl, Bernhard Sick, Sven Tomforde:
Novelty detection in continuously changing environments. Future Gener. Comput. Syst. 114: 138-154 (2021) - [j16]Kirstie L. Bellman, Jean Botev, Ada Diaconescu, Lukas Esterle, Christian Gruhl, Christopher Landauer, Peter R. Lewis, Phyllis R. Nelson, Evangelos Pournaras, Anthony Stein, Sven Tomforde:
Self-improving system integration: Mastering continuous change. Future Gener. Comput. Syst. 117: 29-46 (2021) - [j15]Kirstie L. Bellman, Ada Diaconescu, Sven Tomforde:
Special issue on "self-improving self integration". Future Gener. Comput. Syst. 119: 136-139 (2021) - [c113]Sven Tomforde, Martin Goller:
Assessment of Configuration Stability and Variability in Collections of Self-Adaptive Systems. ACSOS-C 2021: 125-130 - [c112]Anthony Stein, Sven Tomforde:
Reflective Learning Classifier Systems for Self-Adaptive and Self-Organising Agents. ACSOS-C 2021: 139-145 - [c111]Ghassan Al-Falouji, Christian Gruhl, Sven Tomforde:
Digital Shadows in Self-Improving System Integration: A Concept U sing Generative Modelling. ACSOS-C 2021: 166-171 - [c110]Lukas Esterle, Cláudio Gomes, Mirgita Frasheri, Henrik Ejersbo, Sven Tomforde, Peter Gorm Larsen:
Digital twins for collaboration and self-integration. ACSOS-C 2021: 172-177 - [c109]Christian Gruhl, Sven Tomforde:
OHODIN - Online Anomaly Detection for Data Streams. ACSOS-C 2021: 193-197 - [c108]Sven Tomforde, Martin Goller:
Beyond Homeostasis: A Novel Approach for Assessing the Stability and Coherence of Self-Adaptive Systems. DASC/PiCom/CBDCom/CyberSciTech 2021: 10-17 - [c107]Colin Clausen, Simon Reichhuber, Ingo Thomsen, Sven Tomforde:
Improvements to Increase the Efficiency of the AlphaZero Algorithm: A Case Study in the Game 'Connect 4'. ICAART (2) 2021: 803-811 - [c106]Simon Reichhuber, Sven Tomforde:
Bet-based Evolutionary Algorithms: Self-improving Dynamics in Offspring Generation. ICAART (2) 2021: 1192-1199 - [c105]Michael Meyer, Georg Kuschk, Sven Tomforde:
Graph Convolutional Networks for 3D Object Detection on Radar Data. ICCVW 2021: 3053-3062 - [c104]Kirstie L. Bellman, Sven Tomforde:
Lifelike Systems Need Some Kind of a Skin: First Thoughts on Cyberskin Capabilities. LIFELIKE 2021 - [c103]Martin Goller, Sven Tomforde:
A Concept for Self-Explanation of Macro-Level Behaviourin Lifelike Computing Systems. LIFELIKE 2021 - [c102]Anthony Stein, Sven Tomforde, Jean Botev, Peter R. Lewis:
Lifelike Computing Systems. LIFELIKE 2021 - [c101]Ingo Thomsen, Sven Tomforde:
Detecting Extended Incidents in Urban Road Networks for Organic Traffic Control Using Density-Based Clustering of Traffic Flows. SMARTGREENS/VEHITS (Selected Papers) 2021: 330-347 - [c100]Ingo Thomsen, Yannick Zapfe, Sven Tomforde:
Urban Traffic Incident Detection for Organic Traffic Control: A Density-based Clustering Approach. VEHITS 2021: 152-160 - [c99]Heiko Hamann, Julian Schwarzat, Ingo Thomsen, Sven Tomforde:
A Self-organising System Combining Self-adaptive Traffic Control and Urban Platooning: A Concept for Autonomous Driving. VEHITS 2021: 429-437 - [e4]Esam El-Araby, Vana Kalogeraki, Danilo Pianini, Frédéric Lassabe, Barry Porter, Sona Ghahremani, Ingrid Nunes, Mohamed Bakhouya, Sven Tomforde:
IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2021, Washington, DC, USA, September 27 - Oct. 1, 2021. IEEE 2021, ISBN 978-1-6654-1261-2 [contents] - [e3]Esam El-Araby, Vana Kalogeraki, Danilo Pianini, Frédéric Lassabe, Barry Porter, Sona Ghahremani, Ingrid Nunes, Mohamed Bakhouya, Sven Tomforde:
IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2021, Companion Volume, Washington, DC, USA, September 27 - Oct. 1, 2021. IEEE 2021, ISBN 978-1-6654-4393-7 [contents] - [e2]Anthony Stein, Sven Tomforde, Jean Botev, Peter R. Lewis:
Joint Proceedings of the LIFELIKE 2020 - 8th Edition in the Evolution of the Workshop Series of Autonomously Learning and Optimizing Systems (SAOS) co-located with 2020 Conference on Artificial Life (ALIFE 2020), Online, July 16th, 2020, and, Online, July 19th, 2021. CEUR Workshop Proceedings 3007, CEUR-WS.org 2021 [contents] - [i6]Inga Löser, Martin Braun, Christian Gruhl, Jan-Hendrik Menke, Bernhard Sick, Sven Tomforde:
Towards Organic Distribution Systems - The Vision of Self-Configuring, Self-Organising, Self-Healing, and Self-Optimising Power Distribution Management. CoRR abs/2112.07507 (2021) - 2020
- [j14]Sven Tomforde, Martin Goller:
To Adapt or Not to Adapt: A Quantification Technique for Measuring an Expected Degree of Self-Adaptation. Comput. 9(1): 21 (2020) - [j13]Sven Tomforde, Timothy Wood, Jan-Philipp Steghöfer:
Introduction to the Special Issue with Selected Papers of The International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS) 2020. ACM Trans. Auton. Adapt. Syst. 15(4): 10e:1-10e:2 (2020) - [c98]Sven Tomforde, Christian Gruhl:
Fairness, Performance, and Robustness: Is There a CAP Theorem for Self-adaptive and Self-organising Systems? ACSOS Companion 2020: 54-59 - [c97]Christian Gruhl, Jörn Schmeißing, Sven Tomforde, Bernhard Sick:
Normal-Wishart Clustering for Novelty Detection. ACSOS Companion 2020: 64-69 - [c96]Simon Reichhuber, Sven Tomforde:
Opportunistic Meta-Learning: A Case Study for Quality Assurance in Industry 4.0 Environments. ACSOS Companion 2020: 76-81 - [c95]Mirko D'Angelo, Sona Ghahremani, Simos Gerasimou, Johannes Grohmann, Ingrid Nunes, Sven Tomforde, Evangelos Pournaras:
Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning. ACSOS Companion 2020: 121-126 - [c94]Martin Goller, Sven Tomforde:
Towards a Continuous Assessment of Stability in (Self-)Adaptation Behaviour. ACSOS Companion 2020: 154-159 - [c93]Sven Tomforde, Christian Gruhl, Bernhard Sick:
A Swarm-fleet Infrastructure as a Scenario for Proactive, Hybrid Adaptation of System Behaviour. ACSOS Companion 2020: 166-169 - [c92]Simon Reichhuber, Sven Tomforde:
Opportunistic Knowledge Adaption in Self-Learning Systems. ACSOS Companion 2020: 246-248 - [c91]Michael Meyer, Georg Kuschk, Sven Tomforde:
Complex-Valued Convolutional Neural Networks for Automotive Scene Classification Based on Range-Beam-Doppler Tensors. ITSC 2020: 1-6 - [e1]André Brinkmann, Wolfgang Karl, Stefan Lankes, Sven Tomforde, Thilo Pionteck, Carsten Trinitis:
Architecture of Computing Systems - ARCS 2020 - 33rd International Conference, Aachen, Germany, May 25-28, 2020, Proceedings. Lecture Notes in Computer Science 12155, Springer 2020, ISBN 978-3-030-52793-8 [contents] - [i5]Mirko D'Angelo, Sona Ghahremani, Simos Gerasimou, Johannes Grohmann, Ingrid Nunes, Sven Tomforde, Evangelos Pournaras:
Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning. CoRR abs/2008.03995 (2020)
2010 – 2019
- 2019
- [j12]Stefan Rudolph, Sven Tomforde, Jörg Hähner:
Mutual Influence-aware Runtime Learning of Self-adaptation Behavior. ACM Trans. Auton. Adapt. Syst. 14(1): 4:1-4:37 (2019) - [c90]Christian Krupitzer, Sven Tomforde:
Organic Computing Doctoral Dissertation Colloquium 2019. GI-Jahrestagung (Workshops) 2019: 467 - [c89]Christian Krupitzer, Sven Tomforde:
The Organic Computing Doctoral Dissertation Colloquium: Status and Overview in 2019. GI-Jahrestagung (Workshops) 2019: 545-554 - [c88]Mirko D'Angelo, Simos Gerasimou, Sona Ghahremani, Johannes Grohmann, Ingrid Nunes, Evangelos Pournaras, Sven Tomforde:
On learning in collective self-adaptive systems: state of practice and a 3D framework. SEAMS@ICSE 2019: 13-24 - [c87]Kirstie L. Bellman, Christian Gruhl, Christopher Landauer, Sven Tomforde:
Self-Improving System Integration - On a Definition and Characteristics of the Challenge. FAS*W@SASO/ICAC 2019: 1-3 - [c86]Veronika Lesch, Christian Krupitzer, Sven Tomforde:
Emerging Self-Integration through Coordination of Autonomous Adaptive Systems. FAS*W@SASO/ICAC 2019: 6-9 - [c85]Anthony Stein, Sven Tomforde:
Transfer Learning is a Crucial Capability of Intelligent Systems Self-Integrating at Runtime. FAS*W@SASO/ICAC 2019: 32-35 - [c84]Chloe M. Barnes, Kirstie L. Bellman, Jean Botev, Ada Diaconescu, Lukas Esterle, Christian Gruhl, Christopher Landauer, Peter R. Lewis, Phyllis R. Nelson, Anthony Stein, Christopher Stewart, Sven Tomforde:
CHARIOT - Towards a Continuous High-Level Adaptive Runtime Integration Testbed. FAS*W@SASO/ICAC 2019: 52-55 - [c83]Sven Tomforde:
From "Normal" to "Abnormal": A Concept for Determining Expected Self-Adaptation Behaviour. FAS*W@SASO/ICAC 2019: 126-129 - [i4]Stefan Rudolph, Sven Tomforde, Jörg Hähner:
On the Detection of Mutual Influences and Their Consideration in Reinforcement Learning Processes. CoRR abs/1905.04205 (2019) - [i3]Tom Hanika, Marek Herde, Jochen Kuhn, Jan Marco Leimeister, Paul Lukowicz, Sarah Oeste-Reiß, Albrecht Schmidt, Bernhard Sick, Gerd Stumme, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. CoRR abs/1905.07264 (2019) - 2018
- [j11]Martin Jänicke, Bernhard Sick, Sven Tomforde:
Self-Adaptive Multi-Sensor Activity Recognition Systems Based on Gaussian Mixture Models. Informatics 5(3): 38 (2018) - [j10]Bernhard Sick, Sarah Oeste-Reiß, Albrecht Schmidt, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning. Inform. Spektrum 41(1): 52-55 (2018) - [j9]Sven Tomforde, Jan Kantert, Christian Müller-Schloer, Sebastian Bödelt, Bernhard Sick:
Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness. Trans. Comput. Collect. Intell. 28: 193-220 (2018) - [c82]Martin Jänicke, Viktor Schmidt, Bernhard Sick, Sven Tomforde, Paul Lukowicz:
Hijacked Smart Devices - Methodical Foundations for Autonomous Theft Awareness based on Activity Recognition and Novelty Detection. ICAART (2) 2018: 131-142 - [c81]Martin Jänicke, Viktor Schmidt, Bernhard Sick, Sven Tomforde, Paul Lukowicz, Jörn Schmeißing:
Smart Device Stealing and CANDIES. ICAART (Revised Selected Papers) 2018: 247-273 - [c80]Adrian Calma, Moritz Stolz, Daniel Kottke, Sven Tomforde, Bernhard Sick:
Active Learning With Realistic Data - A Case Study. IJCNN 2018: 1-8 - [c79]Ada Diaconescu, Sven Tomforde, Christian Müller-Schloer:
Holonic Cellular Automata: Modelling Multi-level Self-organisation of Structure and Behaviour. ALIFE 2018: 186-193 - [c78]Theresa Kromat, Tobias Dehling, Reinhold Haux, Christoph Peters, Bernhard Sick, Sven Tomforde, Klaus-Hendrik Wolf, Ali Sunyaev:
Gestaltungsraum für proaktive Smart Homes zur Gesundheitsförderung. MKWI 2018: 695-707 - [c77]Andreas Jahn, Sven Tomforde, Michel Morold, Klaus David, Bernhard Sick:
Towards Cooperative Self-adapting Activity Recognition. PECCS 2018: 215-222 - [c76]Kirstie L. Bellman, Jean Botev, Ada Diaconescu, Lukas Esterle, Christian Gruhl, Christopher Landauer, Peter R. Lewis, Anthony Stein, Sven Tomforde, Rolf P. Würtz:
Self-Improving System Integration - Status and Challenges after Five Years of SISSY. FAS*W@SASO/ICAC 2018: 160-167 - [c75]Henner Heck, Bernhard Sick, Sven Tomforde:
Security Issues in Self-Improving System Integration - Challenges and Solution Strategies. FAS*W@SASO/ICAC 2018: 176-181 - [c74]Christian Gruhl, Sven Tomforde, Bernhard Sick:
Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. FAS*W@SASO/ICAC 2018: 198-203 - [c73]Anthony Stein, Sven Tomforde, Ada Diaconescu, Jörg Hähner, Christian Müller-Schloer:
A Concept for Proactive Knowledge Construction in Self-Learning Autonomous Systems. FAS*W@SASO/ICAC 2018: 204-213 - 2017
- [b2]Christian Müller-Schloer, Sven Tomforde:
Organic Computing - Technical Systems for Survival in the Real World. Birkhäuser 2017, ISBN 978-3-319-68476-5 - [j8]Jan Kantert, Sven Tomforde, Richard Scharrer, Susanne Weber, Sarah Edenhofer, Christian Müller-Schloer:
Identification and classification of agent behaviour at runtime in open, trust-based organic computing systems. J. Syst. Archit. 75: 68-78 (2017) - [j7]Anthony Stein, Dominik Rauh, Sven Tomforde, Jörg Hähner:
Interpolation in the eXtended Classifier System: An architectural perspective. J. Syst. Archit. 75: 79-94 (2017) - [j6]Kirstie L. Bellman, Jean Botev, Hanno Hildmann, Peter R. Lewis, Stephen Marsh, Jeremy Pitt, Ingo Scholtes, Sven Tomforde:
Socially-Sensitive Systems Design: Exploring Social Potential. IEEE Technol. Soc. Mag. 36(3): 72-80 (2017) - [c72]