Shared autonomous mobility on demand: A learning-based approach and its performance in the presence of traffic congestion
M Guériau, F Cugurullo… - IEEE Intelligent …, 2020 - ieeexplore.ieee.org
Mobility-on-demand (MOD) systems consisting of shared autonomous vehicles (SAVs) are
expected to improve the efficiency of urban transportation through reduced vehicle …
expected to improve the efficiency of urban transportation through reduced vehicle …
Towards a methodology for building dynamic urgent applications on continuum computing platforms
Advanced cyberinfrastructure aims at making the use of streaming data a common practice
in the scientific community. They offer an ecosystem that links data, compute, network, and …
in the scientific community. They offer an ecosystem that links data, compute, network, and …
Combining neural gas and reinforcement learning for adaptive traffic signal control
Travel time of vehicles in urban traffic networks can be reduced by using Adaptive Traffic
Signal Control (ATSC) to change the signal program according to the current traffic situation …
Signal Control (ATSC) to change the signal program according to the current traffic situation …
Towards an Uncertainty-aware Decision Engine for Proactive Self-Protecting Software
R Liu - 2023 IEEE International Conference on Autonomic …, 2023 - ieeexplore.ieee.org
Proactive protection of software systems can be achieved through Moving Target Defense
(MTD) techniques, which are designed based on addressing the questions of what to move …
(MTD) techniques, which are designed based on addressing the questions of what to move …
Adaptation to unknown situations as the holy grail of learning-based self-adaptive systems: Research directions
N Cardozo, I Dusparic - 2021 International Symposium on …, 2021 - ieeexplore.ieee.org
Self-adaptive systems continuously adapt to changes in their execution environment.
Capturing all possible changes to define suitable behaviour beforehand is unfeasible, or …
Capturing all possible changes to define suitable behaviour beforehand is unfeasible, or …
[PDF][PDF] Next Generation Context-oriented Programming: Embracing Dynamic Generation of Adaptations.
N Cardozo, I Dusparic - J. Object Technol., 2022 - researchgate.net
Context-oriented Programming (COP) first appeared in 2005 as a way to enable the
dynamic adaptation of software systems to specific situations in their surrounding …
dynamic adaptation of software systems to specific situations in their surrounding …
Adaptation to unknown situations as the holy grail of learning-based self-adaptive systems: Research directions
I Dusparic, N Cardozo - arXiv preprint arXiv:2103.06908, 2021 - arxiv.org
Self-adaptive systems continuously adapt to changes in their execution environment.
Capturing all possible changes to define suitable behaviour beforehand is unfeasible, or …
Capturing all possible changes to define suitable behaviour beforehand is unfeasible, or …
Reinforcement Learning for Sustainability: Adapting in large-scale heterogeneous dynamic environments
I Dusparic - 2022 IEEE International Conference on Autonomic …, 2022 - ieeexplore.ieee.org
Reinforcement learning (RL) has seen major breakthroughs in the recent years, most
notably outperforming humans Atari, Go, and StarCraft games. RL use is also being …
notably outperforming humans Atari, Go, and StarCraft games. RL use is also being …
Dynamic neighbourhood optimisation for task allocation using multi-agent
N Creech, NC Pacheco, S Miles - arXiv preprint arXiv:2102.08307, 2021 - arxiv.org
In large-scale systems there are fundamental challenges when centralised techniques are
used for task allocation. The number of interactions is limited by resource constraints such …
used for task allocation. The number of interactions is limited by resource constraints such …
Engineering Decentralized Learning in Self-Adaptive Systems
M D'Angelo - 2021 - diva-portal.org
Systems, Linnaeus University Dissertations No 414/2021, ISBN: 978-91-89283-72-5 (print),
978-91-89283-73-2 (pdf). Future computing environments are envisioned to be populated …
978-91-89283-73-2 (pdf). Future computing environments are envisioned to be populated …