The transition to autonomous cars, the redesign of cities and the future of urban sustainability F Cugurullo, RA Acheampong, M Guériau, I Dusparic Urban Geography, 2020 | 160 | 2020 |
Can autonomous vehicles enable sustainable mobility in future cities? Insights and policy challenges from user preferences over different urban transport options RA Acheampong, F Cugurullo, M Gueriau, I Dusparic Cities 112, 103134, 2021 | 150 | 2021 |
Residential Electrical Demand Forecasting in Very Small Scale: An Evaluation of Forecasting Methods A Marinescu, C Harris, I Dusparic, S Clarke, V Cahill | 103 | 2013 |
Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic M Gueriau, I Dusparic 23rd IEEE International Conference on Intelligent Transportation Systems …, 2020 | 89 | 2020 |
Heterogeneous Multi-Agent Deep Reinforcement Learning for Traffic Lights Control. JA Calvo, I Dusparic AICS, 2-13, 2018 | 78 | 2018 |
Multi-agent residential demand response based on load forecasting I Dusparic, C Harris, A Marinescu, V Cahill, S Clarke 2013 1st IEEE conference on technologies for sustainability (SusTech), 90-96, 2013 | 77 | 2013 |
SAMoD: Shared Autonomous Mobility-on-Demand using Decentralized Reinforcement Learning M Gueriau, I Dusparic The 21st IEEE International Conference on Intelligent Transportation Systems …, 2018 | 75 | 2018 |
Prediction-Based Multi-Agent Reinforcement Learning in Inherently Non-Stationary Environments A Marinescu, I Dusparic, S Clarke ACM Transactions on Autonomous and Adaptive Systems (TAAS) 12 (2), 9, 2017 | 69 | 2017 |
Shared Autonomous Mobility-on-Demand: Learning-based approach and its performance in the presence of traffic congestion M Gueriau, F Cugurullo, RA Acheampong, I Dusparic IEEE Intelligent Transportation Systems Magazine, 2020 | 64 | 2020 |
Multi-agent deep reinforcement learning for zero energy communities A Prasad, I Dusparic IEEE ISGT PES Europe 2019, 2019 | 64 | 2019 |
Distributed W-Learning: Multi-policy optimization in self-organizing systems I Dusparic, V Cahill Self-Adaptive and Self-Organizing Systems, 2009. SASO'09. Third IEEE …, 2009 | 57 | 2009 |
Accelerating Learning in Multi-Objective Systems through Transfer Learning A Taylor, I Dusparic, E Galván-López, S Clarke, V Cahill In a Special Session on Learning and Optimization in Multi-Criteria Dynamic …, 2014 | 53 | 2014 |
Residential demand response: Experimental evaluation and comparison of self-organizing techniques I Dusparic, A Taylor, A Marinescu, F Golpayegani, S Clarke Renewable and Sustainable Energy Reviews 80, 1528-1536, 2017 | 46 | 2017 |
Maximizing Renewable Energy Use with Decentralized Residential Demand Response I Dusparic, A Taylor, A Marinescu, V Cahill, S Clarke The First IEEE International Smart Cities Conference (ISC2-2015), 2015 | 42 | 2015 |
Autonomic multi-policy optimization in pervasive systems: Overview and evaluation I Dusparic, V Cahill ACM Transactions on Autonomous and Adaptive Systems (TAAS) 7 (1), 1-25, 2012 | 42 | 2012 |
Transfer Learning in Multi-Agent Systems Through Parallel Transfer A Taylor, I Dusparic, E Galván-López, S Clarke, V Cahill | 41 | 2013 |
Towards Autonomic Urban Traffic Control with Collaborative Multi-Policy Reinforcement Learning I Dusparic, J Monteil, V Cahill IEEE 19th International Conference on Intelligent Transportation Systems …, 2016 | 34 | 2016 |
Multi-agent collaboration for conflict management in residential demand response F Golpayegani, I Dusparic, A Taylor, S Clarke Computer Communications 96, 63-72, 2016 | 29 | 2016 |
REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association B Galkin, E Fonseca, R Amer, LA DaSilva, I Dusparic IEEE Transactions on Vehicular Technology, 2022 | 27 | 2022 |
Extended Variable Speed Limit control using Multi-agent Reinforcement Learning K Kusic, I Dusparic, M Gueriau, M Greguric, E Ivanjko The 23rd IEEE International Conference on Intelligent Transportation Systems …, 2020 | 27 | 2020 |