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 …

Optimal dynamic thermal management for data center via soft actor-critic algorithm with dynamic control interval and combined-value state space

Y Guo, S Qu, C Wang, Z **ng, K Duan - Applied Energy, 2024 - Elsevier
As the scale of data centers continues to expand, the environmental impact of their energy
consumption has become a major concern, highlighting the increasing importance of …

Towards a methodology for building dynamic urgent applications on continuum computing platforms

D Balouek-Thomert, E Caron, L Lefevre… - 2022 First Combined …, 2022 - ieeexplore.ieee.org
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 …

Combining neural gas and reinforcement learning for adaptive traffic signal control

M Miletić, E Ivanjko, S Mandžuka… - 2021 International …, 2021 - ieeexplore.ieee.org
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 …

Sense-making and knowledge construction via constructivist learning paradigm

J Xue, R Lallement, M Morelli - 2024 IEEE 6th International …, 2024 - ieeexplore.ieee.org
The constructivism is a knowledge acquisition theory that describes mechanisms of
information processing behind infants' cognitive development. When infants play with the …

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 …

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 …

[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 …

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 …

[PDF][PDF] Growing Neural Gas in Multi-Agent Reinforcement Learning Adaptive Traffic Signal Control

M Miletić, I Dusparić, E Ivanjko - 2024 - ceur-ws.org
In recent years, there has been a significant increase in research interest in applying
Reinforcement Learning (RL) to Adaptive Traffic Signal Control (ATSC). Urban traffic …