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2020 – today
- 2024
[j25]Ana L. C. Bazzan, Ivana Dusparic, Marin Lujak, Giuseppe Vizzari:
Agents in Traffic and Transportation (ATT 2022): Revised and Extended Papers. AI Commun. 37(2): 185-187 (2024)- [j24]Hélio N. Cunha Neto
, Jernej Hribar, Ivana Dusparic, Natalia Castro Fernandes, Diogo M. F. Mattos:
FedSBS: Federated-Learning participant-selection method for Intrusion Detection Systems. Comput. Networks 244: 110351 (2024) - [j23]Marin Lujak, Ana L. C. Bazzan, Ivana Dusparic, Giuseppe Vizzari:
Guest editorial: Role of agents in traffic and transportation. Comput. Sci. Inf. Syst. 21(1): v-vi (2024) - [j22]Jasmina Gajcin, Ivana Dusparic:
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities. ACM Comput. Surv. 56(9): 219:1-219:33 (2024) - [j21]Bowen Xie, Sheng Chen, Sheng Zhou, Zhisheng Niu, Boris Galkin, Ivana Dusparic:
Learning-Assisted User Scheduling and Beamforming for mmWave Vehicular Networks. IEEE Trans. Veh. Technol. 73(8): 11262-11275 (2024) - [c58]Jasmina Gajcin, Ivana Dusparic:
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning. AAMAS 2024: 632-640 - [c57]Mateo Sanabria, Ivana Dusparic, Nicolás Cardozo:
Learning Recovery Strategies for Dynamic Self-healing in Reactive Systems. SEAMS@ICSE 2024: 133-142 - [i35]Mateo Sanabria, Ivana Dusparic, Nicolás Cardozo:
Learning Recovery Strategies for Dynamic Self-healing in Reactive Systems. CoRR abs/2401.12405 (2024) - [i34]Jasmina Gajcin, Ivana Dusparic:
ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies. CoRR abs/2402.06503 (2024) - [i33]Juan C. Rosero, Ivana Dusparic, Nicolás Cardozo:
Multi-Objective Deep Reinforcement Learning for Optimisation in Autonomous Systems. CoRR abs/2408.01188 (2024) - [i32]Jasmina Gajcin, Jovan Jeromela, Ivana Dusparic:
Semifactual Explanations for Reinforcement Learning. CoRR abs/2409.05435 (2024) - 2023
- [j20]Erika Fonseca, Boris Galkin, Ramy Amer, Luiz A. DaSilva, Ivana Dusparic:
Adaptive Height Optimization for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach. IEEE Access 11: 5966-5980 (2023) - [j19]Hélio N. Cunha Neto, Jernej Hribar, Ivana Dusparic, Diogo Menezes Ferrazani Mattos, Natalia Castro Fernandes:
A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends. IEEE Access 11: 41928-41953 (2023) - [j18]Nicolás Cardozo, Ivana Dusparic:
Auto-COP: Adaptation generation in Context-oriented Programming using Reinforcement Learning options. Inf. Softw. Technol. 164: 107308 (2023) - [j17]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Communication-enabled deep reinforcement learning to optimise energy-efficiency in UAV-assisted networks. Veh. Commun. 43: 100640 (2023) - [c56]Ivana Dusparic, Barry Porter:
Message from the Program Chairs ACSOS 2023. ACSOS-C 2023: xi-xii - [c55]Nicolás Cardozo, Ivana Dusparic, Christian Cabrera:
Prevalence of Code Smells in Reinforcement Learning Projects. CAIN 2023: 37-42 - [c54]Alberto Castagna, Ivana Dusparic:
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning. ECAI 2023: 357-364 - [c53]Jasmina Gajcin, James McCarthy, Rahul Nair, Radu Marinescu, Elizabeth Daly, Ivana Dusparic:
Iterative Reward Shaping Using Human Feedback for Correcting Reward Misspecification. ECAI 2023: 788-794 - [c52]Jernej Hribar, Luke Hackett, Ivana Dusparic:
Deep W-Networks: Solving Multi-Objective Optimisation Problems with Deep Reinforcement Learning. ICAART (2) 2023: 17-26 - [c51]Jean-Baptiste Monteil, George Iosifidis, Ivana Dusparic:
Reservation of Virtualized Resources with Optimistic Online Learning. ICC 2023: 5147-5153 - [c50]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks. WiMob 2023: 267-273 - [i31]Alberto Castagna, Ivana Dusparic:
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning. CoRR abs/2303.01170 (2023) - [i30]Jasmina Gajcin, Ivana Dusparic:
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning. CoRR abs/2303.04475 (2023) - [i29]Jean-Baptiste Monteil, George Iosifidis, Ivana Dusparic:
Reservation of Virtualized Resources with Optimistic Online Learning. CoRR abs/2303.08772 (2023) - [i28]Nicolás Cardozo, Ivana Dusparic, Christian Cabrera:
Prevalence of Code Smells in Reinforcement Learning Projects. CoRR abs/2303.10236 (2023) - [i27]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks. CoRR abs/2306.08785 (2023) - [i26]Jasmina Gajcin, James McCarthy, Rahul Nair, Radu Marinescu, Elizabeth Daly, Ivana Dusparic:
Iterative Reward Shaping using Human Feedback for Correcting Reward Misspecification. CoRR abs/2308.15969 (2023) - 2022
- [j16]Jernej Hribar, Luiz A. DaSilva, Sheng Zhou, Zhiyuan Jiang, Ivana Dusparic:
Timely and sustainable: Utilising correlation in status updates of battery-powered and energy-harvesting sensors using Deep Reinforcement Learning. Comput. Commun. 192: 223-233 (2022) - [j15]Nicolás Cardozo, Ivana Dusparic:
Next Generation Context-oriented Programming: Embracing Dynamic Generation of Adaptations. J. Object Technol. 21(2): 1-6 (2022) - [j14]Danny Weyns, Ilias Gerostathopoulos, Barbora Buhnova, Nicolás Cardozo, Emilia Cioroaica, Ivana Dusparic, Lars Grunske, Pooyan Jamshidi, Christine Julien, Judith Michael, Gabriel A. Moreno, Shiva Nejati, Patrizio Pelliccione, Federico Quin, Genaína Nunes Rodrigues, Bradley R. Schmerl, Marco Vieira, Thomas Vogel, Rebekka Wohlrab:
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation. ACM SIGSOFT Softw. Eng. Notes 47(4): 18-24 (2022) - [j13]Boris Galkin, Erika Fonseca, Ramy Amer, Luiz A. DaSilva, Ivana Dusparic:
REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association. IEEE Trans. Veh. Technol. 71(1): 5-20 (2022) - [j12]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Optimizing Energy Efficiency in UAV-Assisted Networks Using Deep Reinforcement Learning. IEEE Wirel. Commun. Lett. 11(8): 1590-1594 (2022) - [c49]Ivana Dusparic:
Reinforcement Learning for Sustainability: Adapting in large-scale heterogeneous dynamic environments. ACSOS-C 2022: 49-50 - [c48]Jasmina Gajcin, Ivana Dusparic:
ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning. EXTRAAMAS@AAMAS 2022: 38-56 - [c47]Shivani Tomar, Seshu Tirupathi, Dhaval Vinodbhai Salwala, Ivana Dusparic, Elizabeth Daly:
Prequential Model Selection for Time Series Forecasting based on Saliency Maps. IEEE Big Data 2022: 3383-3392 - [c46]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Energy-aware optimization of UAV base stations placement via decentralized multi-agent Q-learning. CCNC 2022: 216-222 - [c45]Alberto Castagna, Ivana Dusparic:
Multi-agent Transfer Learning in Reinforcement Learning-based Ride-sharing Systems. ICAART (2) 2022: 120-130 - [c44]Boris Galkin, Babatunji Omoniwa, Ivana Dusparic:
Multi-Agent Deep Reinforcement Learning For Optimising Energy Efficiency of Fixed-Wing UAV Cellular Access Points. ICC 2022: 1-6 - [c43]Hélio N. Cunha Neto, Ivana Dusparic, Diogo M. F. Mattos, Natalia Castro Fernandes:
FedSA: Accelerating Intrusion Detection in Collaborative Environments with Federated Simulated Annealing. NetSoft 2022: 420-428 - [c42]Jernej Hribar, Ivana Dusparic:
Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network. WCNC 2022: 2547-2552 - [e5]Roberto Casadei, Elisabetta Di Nitto, Ilias Gerostathopoulos, Danilo Pianini, Ivana Dusparic, Timothy Wood, Phyllis R. Nelson, Evangelos Pournaras, Nelly Bencomo, Sebastian Götz, Christian Krupitzer, Claudia Raibulet:
IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2022, Virtual, CA, USA, September 19-23, 2022. IEEE 2022, ISBN 978-1-6654-7137-4 [contents] - [e4]Roberto Casadei, Elisabetta Di Nitto, Ilias Gerostathopoulos, Danilo Pianini, Ivana Dusparic, Timothy Wood, Phyllis R. Nelson, Evangelos Pournaras, Nelly Bencomo, Sebastian Götz, Christian Krupitzer, Claudia Raibulet:
IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022, Virtual, CA, USA, September 19-23, 2022. IEEE 2022, ISBN 978-1-6654-5142-0 [contents] - [e3]Ana Lúcia C. Bazzan, Ivana Dusparic, Marin Lujak, Giuseppe Vizzari:
Twelfth International Workshop on Agents in Traffic and Transportation co-located with the the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022), Vienna, Austria, July 25, 2022. CEUR Workshop Proceedings 3173, CEUR-WS.org 2022 [contents] - [i25]Jernej Hribar, Ivana Dusparic:
Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network. CoRR abs/2201.07308 (2022) - [i24]Jasmina Gajcin, Ivana Dusparic:
ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning. CoRR abs/2203.11211 (2022) - [i23]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Optimising Energy Efficiency in UAV-Assisted Networks using Deep Reinforcement Learning. CoRR abs/2204.01597 (2022) - [i22]Hélio N. Cunha Neto, Ivana Dusparic, Diogo M. F. Mattos, Natalia Castro Fernandes:
FedSA: Accelerating Intrusion Detection in Collaborative Environments with Federated Simulated Annealing. CoRR abs/2205.11519 (2022) - [i21]Danny Weyns, Ilias Gerostathopoulos, Barbora Buhnova, Nicolás Cardozo, Emilia Cioroaica, Ivana Dusparic, Lars Grunske, Pooyan Jamshidi, Christine Julien, Judith Michael, Gabriel A. Moreno, Shiva Nejati, Patrizio Pelliccione, Federico Quin, Genaína Nunes Rodrigues, Bradley R. Schmerl, Marco Vieira, Thomas Vogel, Rebekka Wohlrab:
Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation. CoRR abs/2206.12492 (2022) - [i20]James McCarthy, Rahul Nair, Elizabeth Daly, Radu Marinescu, Ivana Dusparic:
Boolean Decision Rules for Reinforcement Learning Policy Summarisation. CoRR abs/2207.08651 (2022) - [i19]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Communication-Enabled Multi-Agent Decentralised Deep Reinforcement Learning to Optimise Energy-Efficiency in UAV-Assisted Networks. CoRR abs/2210.00041 (2022) - [i18]Jasmina Gajcin, Ivana Dusparic:
Counterfactual Explanations for Reinforcement Learning. CoRR abs/2210.11846 (2022) - [i17]Jernej Hribar, Luke Hackett, Ivana Dusparic:
Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement Learning. CoRR abs/2211.04813 (2022) - [i16]Tom He, Jasmina Gajcin, Ivana Dusparic:
Causal Counterfactuals for Improving the Robustness of Reinforcement Learning. CoRR abs/2211.05551 (2022) - 2021
- [j11]Marin Lujak, Ivana Dusparic, Franziska Klügl, Giuseppe Vizzari:
Agents in Traffic and Transportation (ATT 2020). AI Commun. 34(1): 1-3 (2021) - [j10]Alberto Castagna, Maxime Guériau, Giuseppe Vizzari, Ivana Dusparic:
Demand-responsive rebalancing zone generation for reinforcement learning-based on-demand mobility. AI Commun. 34(1): 73-88 (2021) - [c41]Erika Fonseca, Boris Galkin, Marvin Kelly, Luiz A. DaSilva, Ivana Dusparic:
Mobility for Cellular-Connected UAVs: Challenges for the Network Provider. EuCNC/6G Summit 2021: 136-141 - [c40]Jernej Hribar, Ryoichi Shinkuma, George Iosifidis, Ivana Dusparic:
Analyse or Transmit: Utilising Correlation at the Edge with Deep Reinforcement Learning. GLOBECOM 2021: 1-6 - [c39]Boris Galkin, Erika Fonseca, Gavin Lee, Conor Duff, Marvin Kelly, Edward Emmanuel, Ivana Dusparic:
Experimental Evaluation of a UAV User QoS from a Two-Tier 3.6GHz Spectrum Network. ICC Workshops 2021: 1-6 - [c38]Kresimir Kusic, Edouard Ivanjko, Filip Vrbanic, Martin Greguric, Ivana Dusparic:
Dynamic Variable Speed Limit Zones Allocation Using Distributed Multi-Agent Reinforcement Learning. ITSC 2021: 3238-3245 - [c37]Nicolás Cardozo, Ivana Dusparic:
Adaptation to Unknown Situations as the Holy Grail of Learning-Based Self-Adaptive Systems: Research Directions. SEAMS@ICSE 2021: 252-253 - [i15]Erika Fonseca, Boris Galkin, Marvin Kelly, Luiz A. DaSilva, Ivana Dusparic:
Mobility for Cellular-Connected UAVs: challenges for the network provider. CoRR abs/2102.12899 (2021) - [i14]Nicolás Cardozo, Ivana Dusparic:
Auto-COP: Adaptation Generation in Context-Oriented Programming using Reinforcement Learning Options. CoRR abs/2103.06757 (2021) - [i13]Ivana Dusparic, Nicolás Cardozo:
Adaptation to Unknown Situations as the Holy Grail of Learning-Based Self-Adaptive Systems: Research Directions. CoRR abs/2103.06908 (2021) - [i12]Babatunji Omoniwa, Maxime Guériau, Ivana Dusparic:
A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT. CoRR abs/2106.00654 (2021) - [i11]Babatunji Omoniwa, Boris Galkin, Ivana Dusparic:
Energy-aware placement optimization of UAV base stations via decentralized multi-agent Q-learning. CoRR abs/2106.00845 (2021) - [i10]Jernej Hribar, Ryoichi Shinkuma, George Iosifidis, Ivana Dusparic:
Analyse or Transmit: Utilising Correlation at the Edge with Deep Reinforcement Learning. CoRR abs/2109.14535 (2021) - [i9]Boris Galkin, Babatunji Omoniwa, Ivana Dusparic:
Multi-Agent Deep Reinforcement Learning For Optimising Energy Efficiency of Fixed-Wing UAV Cellular Access Points. CoRR abs/2111.02258 (2021) - [i8]Alberto Castagna, Ivana Dusparic:
Multi-Agent Transfer Learning in Reinforcement Learning-Based Ride-Sharing Systems. CoRR abs/2112.00424 (2021) - [i7]Jasmina Gajcin, Rahul Nair, Tejaswini Pedapati, Radu Marinescu, Elizabeth Daly, Ivana Dusparic:
Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents. CoRR abs/2112.09462 (2021) - 2020
- [j9]Maxime Guériau, Federico Cugurullo, Ransford A. Acheampong, Ivana Dusparic:
Shared Autonomous Mobility on Demand: A Learning-Based Approach and Its Performance in the Presence of Traffic Congestion. IEEE Intell. Transp. Syst. Mag. 12(4): 208-218 (2020) - [c36]Nicolás Cardozo, Ivana Dusparic:
Language Abstractions and Techniques for Developing Collective Adaptive Systems Using Context-oriented Programming. ACSOS Companion 2020: 133-138 - [c35]Andrew Hynes, Elena P. Sapozhnikova, Ivana Dusparic:
Optimising PID Control with Residual Policy Reinforcement Learning. AICS 2020: 277-288 - [c34]Alberto Castagna, Maxime Guériau, Giuseppe Vizzari, Ivana Dusparic:
Demand-Responsive Zone Generation for Real-Time Vehicle Rebalancing in Ride-Sharing Fleets. ATT@ECAI 2020: 47-54 - [c33]Baudouin Dafflon, Maxime Guériau, Yacine Ouzrout, Ivana Dusparic:
Emerging Micro-Communities for Ride-Sharing Enabled Mobility-on-Demand Systems. ATT@ECAI 2020: 63-70 - [c32]Nicolás Cardozo, Ivana Dusparic:
Learning run-time compositions of interacting adaptations. SEAMS@ICSE 2020: 108-114 - [c31]Miller Trujillo, Mario Linares-Vásquez, Camilo Escobar-Velásquez, Ivana Dusparic, Nicolás Cardozo:
Does Neuron Coverage Matter for Deep Reinforcement Learning?: A Preliminary Study. ICSE (Workshops) 2020: 215-220 - [c30]Maxime Guériau, Ivana Dusparic:
Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic. ITSC 2020: 1-8 - [c29]Kresimir Kusic, Ivana Dusparic, Maxime Guériau, Martin Greguric, Edouard Ivanjko:
Extended Variable Speed Limit control using Multi-agent Reinforcement Learning. ITSC 2020: 1-8 - [e2]Ivana Dusparic, Franziska Klügl, Marin Lujak, Giuseppe Vizzari:
Eleventh International Workshop on Agents in Traffic and Transportation co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostela, Spain, September 4, 2020. CEUR Workshop Proceedings 2701, CEUR-WS.org 2020 [contents] - [i6]Erika Fonseca, Boris Galkin, Luiz A. DaSilva, Ivana Dusparic:
Adaptive Height Optimisation for Cellular-Connected UAVs using Reinforcement Learning. CoRR abs/2007.13695 (2020) - [i5]Boris Galkin, Erika Fonseca, Ramy Amer, Luiz A. DaSilva, Ivana Dusparic:
REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association. CoRR abs/2010.01126 (2020) - [i4]Boris Galkin, Erika Fonseca, Gavin Lee, Conor Duff, Marvin Kelly, Edward Emmanuel, Ivana Dusparic:
Experimental Evaluation of a UAV User QoS from a Two-Tier 3.6GHz Spectrum Network. CoRR abs/2011.03236 (2020)
2010 – 2019
- 2019
- [j8]Martin Connolly, Ivana Dusparic, Georgios Iosifidis, Mélanie Bouroche:
Privacy Aware Incentivization for Participatory Sensing. Sensors 19(18): 4049 (2019) - [j7]Fatemeh Golpayegani, Ivana Dusparic, Siobhán Clarke:
Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-Agent Systems. ACM Trans. Intell. Syst. Technol. 10(3): 31:1-31:31 (2019) - [c28]Christopher Doyle, Maxime Guériau, Ivana Dusparic:
Variational Policy Chaining for Lifelong Reinforcement Learning. ICTAI 2019: 1546-1550 - [c27]Adam Taylor, Ivana Dusparic, Maxime Guériau, Siobhán Clarke:
Parallel Transfer Learning in Multi-Agent Systems: What, when and how to transfer? IJCNN 2019: 1-8 - [c26]Amit Prasad, Ivana Dusparic:
Multi-agent Deep Reinforcement Learning for Zero Energy Communities. ISGT Europe 2019: 1-5 - [c25]Maxime Guériau, Nicolás Cardozo, Ivana Dusparic:
Constructivist Approach to State Space Adaptation in Reinforcement Learning. SASO 2019: 52-61 - [c24]Babatunji Omoniwa, Maxime Guériau, Ivana Dusparic:
An RL-based Approach to Improve Communication Performance and Energy Utilization in Fog-based IoT. WiMob 2019: 324-329 - 2018
- [j6]Stefano Bennati, Ivana Dusparic, Rhythima Shinde, Catholijn M. Jonker:
Volunteers in the Smart City: Comparison of Contribution Strategies on Human-Centered Measures. Sensors 18(11): 3707 (2018) - [j5]Fatemeh Golpayegani, Zahra Sahaf, Ivana Dusparic, Siobhán Clarke:
Participant Selection for Short-term Collaboration in Open Multi-agent systems. Simul. Model. Pract. Theory 83: 149-161 (2018) - [j4]Martin Connolly, Ivana Dusparic, Georgios Iosifidis, Mélanie Bouroche:
Adaptive Reward Allocation for Participatory Sensing. Wirel. Commun. Mob. Comput. 2018: 6353425:1-6353425:15 (2018) - [c23]Jeancarlo Arguello Calvo, Ivana Dusparic:
Heterogeneous Multi-Agent Deep Reinforcement Learning for Traffic Lights Control. AICS 2018: 2-13 - [c22]Martin Connolly, Ivana Dusparic, Mélanie Bouroche:
An Identity Privacy Preserving Incentivization Scheme for Participatory Sensing. ICMU 2018: 1-6 - [c21]Maxime Guériau, Ivana Dusparic:
SAMoD: Shared Autonomous Mobility-on-Demand using Decentralized Reinforcement Learning. ITSC 2018: 1558-1563 - [e1]Ana Lúcia C. Bazzan, Luca Crociani, Ivana Dusparic, Sascha Ossowski:
Proceedings of the Tenth International Workshop on Agents in Traffic and Transportation (ATT 2018) co-located with with the Federated Artificial Intelligence Meeting, including ECAI/IJCAI, AAMAS and ICML 2018 conferences (FAIM 2018), Stockholm, Sweden, July 14, 2018. CEUR Workshop Proceedings 2129, CEUR-WS.org 2018 [contents] - [i3]Stefano Bennati, Ivana Dusparic, Rhythima Shinde, Catholijn M. Jonker:
Volunteers in the Smart City: Comparison of Contribution Strategies on Human-Centered Measures. CoRR abs/1805.09090 (2018) - [i2]Amit Prasad, Ivana Dusparic:
Multi-agent Deep Reinforcement Learning for Zero Energy Communities. CoRR abs/1810.03679 (2018) - 2017
- [j3]Andrei Marinescu, Ivana Dusparic, Siobhán Clarke:
Prediction-Based Multi-Agent Reinforcement Learning in Inherently Non-Stationary Environments. ACM Trans. Auton. Adapt. Syst. 12(2): 9:1-9:23 (2017) - [c20]Nicolás Cardozo, Ivana Dusparic, Jorge H. Castro:
Peace COrP: learning to solve conflicts between contexts. COP@ECOOP 2017: 1-6 - 2016
- [j2]Fatemeh Golpayegani, Ivana Dusparic, Adam Taylor, Siobhán Clarke:
Multi-agent Collaboration for Conflict Management in Residential Demand Response. Comput. Commun. 96: 63-72 (2016) - [c19]Ivana Dusparic, Julien Monteil, Vinny Cahill:
Towards autonomic urban traffic control with collaborative multi-policy reinforcement learning. ITSC 2016: 2065-2070 - 2015
- [c18]Andrei Marinescu, Ivana Dusparic, Adam Taylor, Vinny Cahill, Siobhán Clarke:
P-MARL: Prediction-Based Multi-Agent Reinforcement Learning for Non-Stationary Environments. AAMAS 2015: 1897-1898 - [c17]Fatemeh Golpayegani, Ivana Dusparic, Siobhán Clarke:
Collaborative, parallel Monte Carlo Tree Search for autonomous electricity demand management. SustainIT 2015: 1-8 - [c16]Ivana Dusparic, Adam Taylor, Andrei Marinescu, Vinny Cahill, Siobhán Clarke:
Maximizing renewable energy use with decentralized residential demand response. ISC2 2015: 1-6 - [c15]Jean Cavallo, Andrei Marinescu, Ivana Dusparic, Siobhán Clarke:
Evaluation of Forecasting Methods for Very Small-Scale Networks. DARE 2015: 56-75 - 2014
- [c14]Adam Taylor, Ivana Dusparic, Edgar Galván López, Siobhán Clarke, Vinny Cahill:
Accelerating Learning in multi-objective systems through Transfer Learning. IJCNN 2014: 2298-2305 - [c13]Andrei Marinescu, Ivana Dusparic, Colin Harris, Vinny Cahill, Siobhán Clarke:
A dynamic forecasting method for small scale residential electrical demand. IJCNN 2014: 3767-3774 - [c12]Colin Harris, Ivana Dusparic, Edgar Galván López, Andrei Marinescu, Vinny Cahill, Siobhán Clarke:
Set point control for charging of electric vehicles on the distribution network. ISGT 2014: 1-5 - [c11]Andrei Marinescu, Colin Harris, Ivana Dusparic, Vinny Cahill, Siobhán Clarke:
A hybrid approach to very small scale electrical demand forecasting. ISGT 2014: 1-5 - [i1]Andrei Marinescu, Ivana Dusparic, Adam Taylor, Vinny Cahill, Siobhán Clarke:
Decentralised Multi-Agent Reinforcement Learning for Dynamic and Uncertain Environments. CoRR abs/1409.4561 (2014) - 2013
- [c10]Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhán Clarke, Vinny Cahill:
Residential electrical demand forecasting in very small scale: An evaluation of forecasting methods. SE4SG@ICSE 2013: 25-32 - 2012
- [j1]Ivana Dusparic, Vinny Cahill:
Autonomic multi-policy optimization in pervasive systems: Overview and evaluation. ACM Trans. Auton. Adapt. Syst. 7(1): 11:1-11:25 (2012) - [c9]Edgar Galván, Colin Harris, Ivana Dusparic, Siobhán Clarke, Vinny Cahill:
Reducing electricity costs in a dynamic pricing environment. SmartGridComm 2012: 169-174 - 2010
- [b1]Ivana Dusparic:
Multi-policy optimization in decentralized autonomic systems. Trinity College Dublin, Ireland, 2010
2000 – 2009
- 2009
- [c8]Ivana Dusparic, Vinny Cahill:
Multi-policy optimization in decentralized autonomic systems. AAMAS (2) 2009: 1203-1204 - [c7]Ivana Dusparic, Vinny Cahill:
Using Reinforcement Learning for Multi-policy Optimization in Decentralized Autonomic Systems - An Experimental Evaluation. ATC 2009: 105-119 - [c6]Ivana Dusparic, Vinny Cahill:
Using distributed w-learning for multi-policy optimization in decentralized autonomic systems. ICAC 2009: 63-64 - [c5]Ivana Dusparic, Vinny Cahill:
Distributed W-Learning: Multi-Policy Optimization in Self-Organizing Systems. SASO 2009: 20-29 - [c4]Ivana Dusparic, Vinny Cahill:
Multi-policy Optimization in Self-organizing Systems. SOAR 2009: 101-126 - 2007
- [c3]Ivana Dusparic, Vinny Cahill:
Research Issues in Multiple Policy Optimization Using Collaborative Reinforcement Learning. SEAMS 2007: 18 - 2005
- [c2]Ivana Dusparic, Dominik Dahlem, Jim Dowling:
Flexible Application Rights Management in a Pervasive Environment. EEE 2005: 680-685 - 2004
- [c1]Dominik Dahlem, Ivana Dusparic, Jim Dowling:
A Pervasive Application Rights Management Architecture (PARMA) based on ODRL. ODRL Workshop 2004: 45-63
Coauthor Index
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, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-21 21:29 CEST by the dblp team
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