A Pervasive Application Rights Management Architecture (PARMA) based on ODRL. - Dominik Dahlem; Ivana Dusparic; Jim Dowling (ODRL Workshop, 2004)

Flexible Application Rights Management in a Pervasive Environment. - Ivana Dusparic; Dominik Dahlem; Jim Dowling (EEE, 2005)

Research Issues in Multiple Policy Optimization Using Collaborative Reinforcement Learning. - Ivana Dusparic; Vinny Cahill (SEAMS, 2007)

Multi-policy optimization in decentralized autonomic systems. - Ivana Dusparic; Vinny Cahill (AAMAS (2), 2009)

Using Reinforcement Learning for Multi-policy Optimization in Decentralized Autonomic Systems - An Experimental Evaluation. - Ivana Dusparic; Vinny Cahill (ATC, 2009)

Using distributed w-learning for multi-policy optimization in decentralized autonomic systems. - Ivana Dusparic; Vinny Cahill (ICAC, 2009)

Distributed W-Learning: Multi-Policy Optimization in Self-Organizing Systems. - Ivana Dusparic; Vinny Cahill (SASO, 2009)

Multi-policy Optimization in Self-organizing Systems. - Ivana Dusparic; Vinny Cahill (SOAR, 2009)

Multi-policy optimization in decentralized autonomic systems - Ivana Dusparic (2010)

Reducing electricity costs in a dynamic pricing environment. - Edgar Galván; Colin Harris; Ivana Dusparic; Siobhán Clarke; Vinny Cahill (SmartGridComm, 2012)

Autonomic multi-policy optimization in pervasive systems: Overview and evaluation. - Ivana Dusparic; Vinny Cahill (ACM Trans. Auton. Adapt. Syst., 2012)

Residential electrical demand forecasting in very small scale: An evaluation of forecasting methods. - Andrei Marinescu; Colin Harris; Ivana Dusparic; Siobhán Clarke; Vinny Cahill (SE4SG@ICSE, 2013)

A dynamic forecasting method for small scale residential electrical demand. - Andrei Marinescu; Ivana Dusparic; Colin Harris; Vinny Cahill; Siobhán Clarke (IJCNN, 2014)

Accelerating Learning in multi-objective systems through Transfer Learning. - Adam Taylor; Ivana Dusparic; Edgar Galván López; Siobhán Clarke; Vinny Cahill (IJCNN, 2014)

Set point control for charging of electric vehicles on the distribution network. - Colin Harris; Ivana Dusparic; Edgar Galván López; Andrei Marinescu; Vinny Cahill; Siobhán Clarke (ISGT, 2014)

A hybrid approach to very small scale electrical demand forecasting. - Andrei Marinescu; Colin Harris; Ivana Dusparic; Vinny Cahill; Siobhán Clarke (ISGT, 2014)

Decentralised Multi-Agent Reinforcement Learning for Dynamic and Uncertain Environments. - Andrei Marinescu; Ivana Dusparic; Adam Taylor; Vinny Cahill; Siobhán Clarke (CoRR, 2014)

P-MARL: Prediction-Based Multi-Agent Reinforcement Learning for Non-Stationary Environments. - Andrei Marinescu; Ivana Dusparic; Adam Taylor; Vinny Cahill; Siobhán Clarke (AAMAS, 2015)

Collaborative, parallel Monte Carlo Tree Search for autonomous electricity demand management. - Fatemeh Golpayegani; Ivana Dusparic; Siobhán Clarke (SustainIT, 2015)

Maximizing renewable energy use with decentralized residential demand response. - Ivana Dusparic; Adam Taylor; Andrei Marinescu; Vinny Cahill; Siobhán Clarke (ISC2, 2015)

Evaluation of Forecasting Methods for Very Small-Scale Networks. - Jean Cavallo; Andrei Marinescu; Ivana Dusparic; Siobhán Clarke (DARE, 2015)

Towards autonomic urban traffic control with collaborative multi-policy reinforcement learning. - Ivana Dusparic; Julien Monteil; Vinny Cahill (ITSC, 2016)

Multi-agent Collaboration for Conflict Management in Residential Demand Response. - Fatemeh Golpayegani; Ivana Dusparic; Adam Taylor; Siobhán Clarke (Comput. Commun., 2016)

Peace COrP: learning to solve conflicts between contexts. - Nicolás Cardozo; Ivana Dusparic; Jorge H. Castro (COP@ECOOP, 2017)

Prediction-Based Multi-Agent Reinforcement Learning in Inherently Non-Stationary Environments. - Andrei Marinescu; Ivana Dusparic; Siobhán Clarke (ACM Trans. Auton. Adapt. Syst., 2017)

Heterogeneous Multi-Agent Deep Reinforcement Learning for Traffic Lights Control. - Jeancarlo Arguello Calvo; Ivana Dusparic (AICS, 2018)

An Identity Privacy Preserving Incentivization Scheme for Participatory Sensing. - Martin Connolly; Ivana Dusparic; Mélanie Bouroche (ICMU, 2018)

SAMoD: Shared Autonomous Mobility-on-Demand using Decentralized Reinforcement Learning. - Maxime Guériau; Ivana Dusparic (ITSC, 2018)

Volunteers in the Smart City: Comparison of Contribution Strategies on Human-Centered Measures. - Stefano Bennati; Ivana Dusparic; Rhythima Shinde; Catholijn M. Jonker (Sensors, 2018)

Participant Selection for Short-term Collaboration in Open Multi-agent systems. - Fatemeh Golpayegani; Zahra Sahaf; Ivana Dusparic; Siobhán Clarke (Simul. Model. Pract. Theory, 2018)

Adaptive Reward Allocation for Participatory Sensing. - Martin Connolly; Ivana Dusparic; Georgios Iosifidis; Mélanie Bouroche (Wirel. Commun. Mob. Comput., 2018)

Variational Policy Chaining for Lifelong Reinforcement Learning. - Christopher Doyle; Maxime Guériau; Ivana Dusparic (ICTAI, 2019)

Parallel Transfer Learning in Multi-Agent Systems: What, when and how to transfer? - Adam Taylor; Ivana Dusparic; Maxime Guériau; Siobhán Clarke (IJCNN, 2019)

Multi-agent Deep Reinforcement Learning for Zero Energy Communities. - Amit Prasad; Ivana Dusparic (ISGT Europe, 2019)

Constructivist Approach to State Space Adaptation in Reinforcement Learning. - Maxime Guériau; Nicolás Cardozo; Ivana Dusparic (SASO, 2019)

An RL-based Approach to Improve Communication Performance and Energy Utilization in Fog-based IoT. - Babatunji Omoniwa; Maxime Guériau; Ivana Dusparic (WiMob, 2019)

Privacy Aware Incentivization for Participatory Sensing. - Martin Connolly; Ivana Dusparic; Georgios Iosifidis; Mélanie Bouroche (Sensors, 2019)

Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-Agent Systems. - Fatemeh Golpayegani; Ivana Dusparic; Siobhán Clarke (ACM Trans. Intell. Syst. Technol., 2019)

Language Abstractions and Techniques for Developing Collective Adaptive Systems Using Context-oriented Programming. - Nicolás Cardozo; Ivana Dusparic (ACSOS Companion, 2020)

Optimising PID Control with Residual Policy Reinforcement Learning. - Andrew Hynes; Elena P. Sapozhnikova; Ivana Dusparic (AICS, 2020)

Demand-Responsive Zone Generation for Real-Time Vehicle Rebalancing in Ride-Sharing Fleets. - Alberto Castagna; Maxime Guériau; Giuseppe Vizzari; Ivana Dusparic (ATT@ECAI, 2020)

Emerging Micro-Communities for Ride-Sharing Enabled Mobility-on-Demand Systems. - Baudouin Dafflon; Maxime Guériau; Yacine Ouzrout; Ivana Dusparic (ATT@ECAI, 2020)

Learning run-time compositions of interacting adaptations. - Nicolás Cardozo; Ivana Dusparic (SEAMS@ICSE, 2020)

Does Neuron Coverage Matter for Deep Reinforcement Learning?: A Preliminary Study. - Miller Trujillo; Mario Linares-Vásquez; Camilo Escobar-Velásquez; Ivana Dusparic; Nicolás Cardozo (ICSE (Workshops), 2020)

Quantifying the impact of connected and autonomous vehicles on traffic efficiency and safety in mixed traffic. - Maxime Guériau; Ivana Dusparic (ITSC, 2020)

Extended Variable Speed Limit control using Multi-agent Reinforcement Learning. - Kresimir Kusic; Ivana Dusparic; Maxime Guériau; Martin Greguric; Edouard Ivanjko (ITSC, 2020)

Adaptive Height Optimisation for Cellular-Connected UAVs using Reinforcement Learning. - Erika Fonseca; Boris Galkin; Luiz A. DaSilva; Ivana Dusparic (CoRR, 2020)

Shared Autonomous Mobility on Demand: A Learning-Based Approach and Its Performance in the Presence of Traffic Congestion. - Maxime Guériau; Federico Cugurullo; Ransford A. Acheampong; Ivana Dusparic (IEEE Intell. Transp. Syst. Mag., 2020)

Mobility for Cellular-Connected UAVs: Challenges for the Network Provider. - Erika Fonseca; Boris Galkin; Marvin Kelly; Luiz A. DaSilva; Ivana Dusparic (EuCNC/6G Summit, 2021)

Analyse or Transmit: Utilising Correlation at the Edge with Deep Reinforcement Learning. - Jernej Hribar; Ryoichi Shinkuma; George Iosifidis; Ivana Dusparic (GLOBECOM, 2021)

Experimental Evaluation of a UAV User QoS from a Two-Tier 3.6GHz Spectrum Network. - Boris Galkin; Erika Fonseca; Gavin Lee; Conor Duff; Marvin Kelly; Edward Emmanuel; Ivana Dusparic (ICC Workshops, 2021)

Dynamic Variable Speed Limit Zones Allocation Using Distributed Multi-Agent Reinforcement Learning. - Kresimir Kusic; Edouard Ivanjko; Filip Vrbanic; Martin Greguric; Ivana Dusparic (ITSC, 2021)

Adaptation to Unknown Situations as the Holy Grail of Learning-Based Self-Adaptive Systems: Research Directions. - Nicolás Cardozo; Ivana Dusparic (SEAMS@ICSE, 2021)

Demand-responsive rebalancing zone generation for reinforcement learning-based on-demand mobility. - Alberto Castagna; Maxime Guériau; Giuseppe Vizzari; Ivana Dusparic (AI Commun., 2021)

Agents in Traffic and Transportation (ATT 2020). - Marin Lujak; Ivana Dusparic; Franziska Klügl; Giuseppe Vizzari (AI Commun., 2021)

A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT. - Babatunji Omoniwa; Maxime Guériau; Ivana Dusparic (CoRR, 2021)

Energy-aware placement optimization of UAV base stations via decentralized multi-agent Q-learning. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (CoRR, 2021)

Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents. - Jasmina Gajcin; Rahul Nair; Tejaswini Pedapati; Radu Marinescu 002; Elizabeth Daly; Ivana Dusparic (CoRR, 2021)

Reinforcement Learning for Sustainability: Adapting in large-scale heterogeneous dynamic environments. - Ivana Dusparic (ACSOS-C, 2022)

ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning. - Jasmina Gajcin; Ivana Dusparic (EXTRAAMAS@AAMAS, 2022)

Prequential Model Selection for Time Series Forecasting based on Saliency Maps. - Shivani Tomar; Seshu Tirupathi; Dhaval Vinodbhai Salwala; Ivana Dusparic; Elizabeth Daly (IEEE Big Data, 2022)

Energy-aware optimization of UAV base stations placement via decentralized multi-agent Q-learning. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (CCNC, 2022)

Multi-agent Transfer Learning in Reinforcement Learning-based Ride-sharing Systems. - Alberto Castagna; Ivana Dusparic (ICAART (2), 2022)

Multi-Agent Deep Reinforcement Learning For Optimising Energy Efficiency of Fixed-Wing UAV Cellular Access Points. - Boris Galkin; Babatunji Omoniwa; Ivana Dusparic (ICC, 2022)

FedSA: Accelerating Intrusion Detection in Collaborative Environments with Federated Simulated Annealing. - Hélio N. Cunha Neto; Ivana Dusparic; Diogo M. F. Mattos; Natalia Castro Fernandes (NetSoft, 2022)

Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network. - Jernej Hribar; Ivana Dusparic (WCNC, 2022)

Timely and sustainable: Utilising correlation in status updates of battery-powered and energy-harvesting sensors using Deep Reinforcement Learning. - Jernej Hribar; Luiz A. DaSilva; Sheng Zhou 001; Zhiyuan Jiang; Ivana Dusparic (Comput. Commun., 2022)

Optimising Energy Efficiency in UAV-Assisted Networks using Deep Reinforcement Learning. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (CoRR, 2022)

Boolean Decision Rules for Reinforcement Learning Policy Summarisation. - James McCarthy; Rahul Nair; Elizabeth Daly; Radu Marinescu 002; Ivana Dusparic (CoRR, 2022)

Communication-Enabled Multi-Agent Decentralised Deep Reinforcement Learning to Optimise Energy-Efficiency in UAV-Assisted Networks. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (CoRR, 2022)

Counterfactual Explanations for Reinforcement Learning. - Jasmina Gajcin; Ivana Dusparic (CoRR, 2022)

Causal Counterfactuals for Improving the Robustness of Reinforcement Learning. - Tom He; Jasmina Gajcin; Ivana Dusparic (CoRR, 2022)

Next Generation Context-oriented Programming: Embracing Dynamic Generation of Adaptations. - Nicolás Cardozo; Ivana Dusparic (J. Object Technol., 2022)

Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation. - Danny Weyns; Ilias Gerostathopoulos; Barbora Buhnova; Nicolás Cardozo; Emilia Cioroaica; Ivana Dusparic; Lars Grunske; Pooyan Jamshidi; Christine Julien 001; Judith Michael; Gabriel A. Moreno; Shiva Nejati 001; et al. (ACM SIGSOFT Softw. Eng. Notes, 2022)

REQIBA: Regression and Deep Q-Learning for Intelligent UAV Cellular User to Base Station Association. - Boris Galkin; Erika Fonseca; Ramy Amer; Luiz A. DaSilva; Ivana Dusparic (IEEE Trans. Veh. Technol., 2022)

Optimizing Energy Efficiency in UAV-Assisted Networks Using Deep Reinforcement Learning. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (IEEE Wirel. Commun. Lett., 2022)

Message from the Program Chairs ACSOS 2023. - Ivana Dusparic; Barry Porter (ACSOS-C, 2023)

Prevalence of Code Smells in Reinforcement Learning Projects. - Nicolás Cardozo; Ivana Dusparic; Christian Cabrera 001 (CAIN, 2023)

Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning. - Alberto Castagna; Ivana Dusparic (ECAI, 2023)

Iterative Reward Shaping Using Human Feedback for Correcting Reward Misspecification. - Jasmina Gajcin; James McCarthy; Rahul Nair; Radu Marinescu 002; Elizabeth Daly; Ivana Dusparic (ECAI, 2023)

Deep W-Networks: Solving Multi-Objective Optimisation Problems with Deep Reinforcement Learning. - Jernej Hribar; Luke Hackett; Ivana Dusparic (ICAART (2), 2023)

Reservation of Virtualized Resources with Optimistic Online Learning. - Jean-Baptiste Monteil; George Iosifidis; Ivana Dusparic (ICC, 2023)

Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (WiMob, 2023)

Adaptive Height Optimization for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach. - Erika Fonseca; Boris Galkin; Ramy Amer; Luiz A. DaSilva; Ivana Dusparic (IEEE Access, 2023)

A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends. - Hélio N. Cunha Neto; Jernej Hribar; Ivana Dusparic; Diogo Menezes Ferrazani Mattos; Natalia Castro Fernandes (IEEE Access, 2023)

Communication-enabled deep reinforcement learning to optimise energy-efficiency in UAV-assisted networks. - Babatunji Omoniwa; Boris Galkin; Ivana Dusparic (Veh. Commun., 2023)

Auto-COP: Adaptation generation in Context-oriented Programming using Reinforcement Learning options. - Nicolás Cardozo; Ivana Dusparic (Inf. Softw. Technol., 2023)

Multi-Objective Deep Reinforcement Learning Optimisation in Autonomous Systems. - Juan C. Rosero; Nicolás Cardozo; Ivana Dusparic (ACSOS-C, 2024)

RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning. - Jasmina Gajcin; Ivana Dusparic (AAMAS, 2024)

Growing Neural Gas in Multi-Agent Reinforcement Learning Adaptive Traffic Signal Control. - Mladen Miletic; Ivana Dusparic; Edouard Ivanjko (ATT@ECAI, 2024)

Towards 6G for Connected Autonomous Vehicles: A Trial Facility Analysis. - Shih-Kai Chou; Jernej Hribar; Ivana Dusparic; Carolina Fortuna (CAMAD, 2024)

Semifactual Explanations for Reinforcement Learning. - Jasmina Gajcin; Jovan Jeromela; Ivana Dusparic (HAI, 2024)

Applying Neural Monte Carlo Tree Search to Unsignalized Multi-intersection Scheduling for Autonomous Vehicles. - Yucheng Shi; Wenlong Wang; Xiaowen Tao; Ivana Dusparic; Vinny Cahill (IROS, 2024)

Learning Recovery Strategies for Dynamic Self-healing in Reactive Systems. - Mateo Sanabria; Ivana Dusparic; Nicolás Cardozo (SEAMS@ICSE, 2024)

Agents in Traffic and Transportation (ATT 2022): Revised and Extended Papers. - Ana L. C. Bazzan; Ivana Dusparic; Marin Lujak; Giuseppe Vizzari (AI Commun., 2024)

FedSBS: Federated-Learning participant-selection method for Intrusion Detection Systems. - Hélio N. Cunha Neto; Jernej Hribar; Ivana Dusparic; Natalia Castro Fernandes; Diogo M. F. Mattos (Comput. Networks, 2024)

Guest editorial: Role of agents in traffic and transportation. - Marin Lujak; Ana L. C. Bazzan; Ivana Dusparic; Giuseppe Vizzari (Comput. Sci. Inf. Syst., 2024)

ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies. - Jasmina Gajcin; Ivana Dusparic (CoRR, 2024)

Learning-Assisted User Scheduling and Beamforming for mmWave Vehicular Networks. - Bowen Xie; Sheng Chen 013; Sheng Zhou 001; Zhisheng Niu; Boris Galkin; Ivana Dusparic (IEEE Trans. Veh. Technol., 2024)

Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities. - Jasmina Gajcin; Ivana Dusparic (ACM Comput. Surv., 2024)

Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient. - Wenlong Wang; Ivana Dusparic; Yucheng Shi; Ke Zhang; Vinny Cahill (ICLR, 2025)

Towards Personalised and User-Friendly Counterfactual Sequences for Failure Correction. - Jasmina Gajcin; Jovan Jeromela; Ivana Dusparic (UMAP (Adjunct Publication), 2025)

Optimistic Exploration for Risk-Averse Constrained Reinforcement Learning. - James McCarthy; Radu Marinescu 002; Elizabeth Daly; Ivana Dusparic (CoRR, 2025)