By Dr Francisco Cruz Naranjo

Book Chapters

Cruz F; Dazeley R; Vamplew P, 2019, 'Memory-Based Explainable Reinforcement Learning', in , pp. 66 - 77, http://dx.doi.org/10.1007/978-3-030-35288-2_6

Journal articles

Ly A; Dazeley R; Vamplew P; Cruz F; Aryal S, 2024, 'Elastic step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks', Neurocomputing, 576, http://dx.doi.org/10.1016/j.neucom.2023.127170

Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2023, 'Persistent rule-based interactive reinforcement learning', Neural Computing and Applications, 35, pp. 23411 - 23428, http://dx.doi.org/10.1007/s00521-021-06466-w

Cruz F; Dazeley R; Vamplew P; Moreira I, 2023, 'Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario', Neural Computing and Applications, 35, pp. 18113 - 18130, http://dx.doi.org/10.1007/s00521-021-06425-5

Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2023, 'Human engagement providing evaluative and informative advice for interactive reinforcement learning', Neural Computing and Applications, 35, pp. 18215 - 18230, http://dx.doi.org/10.1007/s00521-021-06850-6

Harland H; Dazeley R; Nakisa B; Cruz F; Vamplew P, 2023, 'AI apology: interactive multi-objective reinforcement learning for human-aligned AI', Neural Computing and Applications, 35, pp. 16917 - 16930, http://dx.doi.org/10.1007/s00521-023-08586-x

Dazeley R; Vamplew P; Cruz F, 2023, 'Explainable reinforcement learning for broad-XAI: a conceptual framework and survey', Neural Computing and Applications, 35, pp. 16893 - 16916, http://dx.doi.org/10.1007/s00521-023-08423-1

Cruz F; Karimpanal TG; Solis MA; Barros P; Dazeley R, 2023, 'Human-aligned reinforcement learning for autonomous agents and robots', Neural Computing and Applications, 35, pp. 16689 - 16691, http://dx.doi.org/10.1007/s00521-023-08748-x

Millán-Arias C; Fernandes B; Cruz F, 2023, 'Proxemic behavior in navigation tasks using reinforcement learning', Neural Computing and Applications, 35, pp. 16723 - 16738, http://dx.doi.org/10.1007/s00521-022-07628-0

de Andrade JVR; Fernandes BJT; Izídio ARLC; da Silva Filho NM; Cruz F, 2023, 'Vessel Velocity Estimation and Docking Analysis: A Computer Vision Approach', Algorithms, 16, http://dx.doi.org/10.3390/a16070326

Bignold A; Cruz F; Taylor ME; Brys T; Dazeley R; Vamplew P; Foale C, 2023, 'A conceptual framework for externally-influenced agents: an assisted reinforcement learning review', Journal of Ambient Intelligence and Humanized Computing, 14, pp. 3621 - 3644, http://dx.doi.org/10.1007/s12652-021-03489-y

Nguyen HS; Cruz F; Dazeley R, 2023, 'Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments', Sensors, 23, http://dx.doi.org/10.3390/s23052681

Cruz F; Solis MA; Navarro-Guerrero N, 2023, 'Editorial: Cognitive inspired aspects of robot learning', Frontiers in Neurorobotics, 17, http://dx.doi.org/10.3389/fnbot.2023.1256788

Azevedo GODA; Fernandes BJT; Silva LHDS; Freire A; de Araújo RP; Cruz F, 2022, 'Event-Based Angular Speed Measurement and Movement Monitoring', Sensors, 22, http://dx.doi.org/10.3390/s22207963

Portugal E; Cruz F; Ayala A; Fernandes B, 2022, 'Analysis of Explainable Goal-Driven Reinforcement Learning in a Continuous Simulated Environment', Algorithms, 15, http://dx.doi.org/10.3390/a15030091

Ayala A; Fernandes BJT; Cruz F; Macedo D; Zanchettin C, 2022, 'Convolution Optimization in Fire Classification', IEEE Access, 10, pp. 23642 - 23658, http://dx.doi.org/10.1109/ACCESS.2022.3151660

Ayala A; Ortiz Figueroa T; Fernandes B; Cruz F, 2021, 'Diabetic retinopathy improved detection using deep learning', Applied Sciences (Switzerland), 11, http://dx.doi.org/10.3390/app112411970

Dazeley R; Vamplew P; Foale C; Young C; Aryal S; Cruz F, 2021, 'Levels of explainable artificial intelligence for human-aligned conversational explanations', Artificial Intelligence, 299, http://dx.doi.org/10.1016/j.artint.2021.103525

Millan-Arias CC; Fernandes BJT; Cruz F; Dazeley R; Fernandes S, 2021, 'A Robust Approach for Continuous Interactive Actor-Critic Algorithms', IEEE Access, 9, pp. 104242 - 104260, http://dx.doi.org/10.1109/ACCESS.2021.3099071

Bignold A; Cruz F; Dazeley R; Vamplew P; Foale C, 2021, 'An evaluation methodology for interactive reinforcement learning with simulated users', Biomimetics, 6, pp. 1 - 15, http://dx.doi.org/10.3390/biomimetics6010013

Contreras R; Ayala A; Cruz F, 2020, 'Unmanned aerial vehicle control through domain-based automatic speech recognition', Computers, 9, pp. 1 - 15, http://dx.doi.org/10.3390/computers9030075

Moreira I; Rivas J; Cruz F; Dazeley R; Ayala A; Fernandes B, 2020, 'Deep reinforcement learning with interactive feedback in a human-robot environment', Applied Sciences (Switzerland), 10, http://dx.doi.org/10.3390/app10165574

Cruz F; Magg S; Nagai Y; Wermter S, 2018, 'Improving interactive reinforcement learning: What makes a good teacher?', Connection Science, 30, pp. 306 - 325, http://dx.doi.org/10.1080/09540091.2018.1443318

Cruz F; Magg S; Weber C; Wermter S, 2016, 'Training Agents With Interactive Reinforcement Learning and Contextual Affordances', IEEE Transactions on Cognitive and Developmental Systems, 8, pp. 271 - 284, http://dx.doi.org/10.1109/TCDS.2016.2543839

Cruz F; Baraglia J; Nagai Y; Wermter S, 2016, 'Special issue on bio-inspired social robot learning in home scenarios', IEEE Transactions on Cognitive and Developmental Systems, 8, pp. 1 - 2, http://dx.doi.org/10.1109/TCDS.2016.2603000

Conference Papers

Ly A; Dazeley R; Vamplew P; Cruz F; Aryal S, 2023, 'Elastic step DDPG: Multi-step reinforcement learning for improved sample efficiency', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN54540.2023.10191774

Lin Z; Cruz F; Sandoval EB, 2023, 'Self context-aware emotion perception on human-robot interaction', in Australasian Conference on Robotics and Automation, ACRA

Portugal E; Ayala A; Cruz F; Fernandes B; Murilo S, 2023, 'Time estimation for deep learning model’s inference in distributed processing units', in 2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023, http://dx.doi.org/10.1109/LA-CCI58595.2023.10409398

Tong Z; Ayala A; Sandoval EB; Cruz F, 2023, 'Urban Autonomous Driving of Emergency Vehicles with Reinforcement Learning', in 2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023, http://dx.doi.org/10.1109/LA-CCI58595.2023.10409469

Schroeter N; Cruz F; Wermter S, 2022, 'Introspection-based Explainable Reinforcement Learning in Episodic and Non-episodic Scenarios', in Australasian Conference on Robotics and Automation, ACRA, Queensland University of Technology (QUT), presented at Australasian Conference on Robotics and Automation, ACRA, Queensland University of Technology (QUT), 06 December 2022 - 08 December 2022, https://ssl.linklings.net/conferences/acra/acra2022_proceedings/views/includes/files/pap114s2.pdf

Cruz F; Young C; Dazeley R; Vamplew P, 2022, 'Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios', in IEEE International Conference on Intelligent Robots and Systems, pp. 894 - 901, http://dx.doi.org/10.1109/IROS47612.2022.9981334

Muñoz H; Portugal E; Ayala A; Fernandes B; Cruz F, 2022, 'Explaining Agent's Decision-making in a Hierarchical Reinforcement Learning Scenario', in Proceedings - International Conference of the Chilean Computer Science Society, SCCC, http://dx.doi.org/10.1109/SCCC57464.2022.10000321

Millán-Arias C; Contreras R; Cruz F; Fernandes B, 2022, 'Reinforcement Learning for UAV control with Policy and Reward Shaping', in Proceedings - International Conference of the Chilean Computer Science Society, SCCC, http://dx.doi.org/10.1109/SCCC57464.2022.10000286

Millán-Arias C; Fernandes B; Cruz F; Dazeley R; Fernandes S, 2020, 'A Robust Approach for Continuous Interactive Reinforcement Learning', in HAI 2020 - Proceedings of the 8th International Conference on Human-Agent Interaction, pp. 278 - 280, http://dx.doi.org/10.1145/3406499.3418769

Ayala A; Cruz F; Campos D; Rubio R; Fernandes B; Dazeley R, 2020, 'A Comparison of Humanoid Robot Simulators: A Quantitative Approach', in ICDL-EpiRob 2020 - 10th IEEE International Conference on Development and Learning and Epigenetic Robotics, http://dx.doi.org/10.1109/ICDL-EpiRob48136.2020.9278116

Barros P; Tanevska A; Cruz F; Sciutti A, 2020, 'Moody Learners-Explaining Competitive Behaviour of Reinforcement Learning Agents', in ICDL-EpiRob 2020 - 10th IEEE International Conference on Development and Learning and Epigenetic Robotics, http://dx.doi.org/10.1109/ICDL-EpiRob48136.2020.9278125

Ayala A; Fernandes B; Cruz F; MacEdo D; Oliveira ALI; Zanchettin C, 2020, 'KutralNet: A Portable Deep Learning Model for Fire Recognition', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN48605.2020.9207202

Ayala A; Lima E; Fernandes B; Bezerra BLD; Cruz F, 2019, 'Lightweight and efficient octave convolutional neural network for fire recognition', in 2019 IEEE LATIN AMERICAN CONFERENCE ON COMPUTATIONAL INTELLIGENCE (LA-CCI), IEEE, ECUADOR, Guayaquil, pp. 87 - 92, presented at IEEE Latin American Conference on Computational Intelligence (LA-CCI), ECUADOR, Guayaquil, 11 November 2019 - 15 November 2019, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000926088100015&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1

Ayala A; Lima E; Fernandes B; Bezerra BLD; Cruz F, 2019, 'Lightweight and efficient octave convolutional neural network for fire recognition', in 2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019, http://dx.doi.org/10.1109/LA-CCI47412.2019.9037059

Cruz F; Wuppen P; Fazrie A; Weber C; Wermter S, 2019, 'Action Selection Methods in a Robotic Reinforcement Learning Scenario', in 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018, http://dx.doi.org/10.1109/LA-CCI.2018.8625243

Ayala A; Henríquez C; Cruz F, 2019, 'Reinforcement learning using continuous states and interactive feedback', in ACM International Conference Proceeding Series, http://dx.doi.org/10.1145/3309772.3309801

Millán C; Fernandes B; Cruz F, 2019, 'Human feedback in continuous actor-critic reinforcement learning', in ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 661 - 666

Cruz F; Parisi GI; Wermter S, 2018, 'Multi-modal Feedback for Affordance-driven Interactive Reinforcement Learning', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN.2018.8489237

Cruz F; Wuppen P; Magg S; Fazrie A; Wermter S, 2017, 'Agent-advising approaches in an interactive reinforcement learning scenario', in 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017, pp. 209 - 214, http://dx.doi.org/10.1109/DEVLRN.2017.8329809

Cruz F; Parisi GI; Twiefel J; Wermter S, 2016, 'Multi-modal integration of dynamic audiovisual patterns for an interactive reinforcement learning scenario', in IEEE International Conference on Intelligent Robots and Systems, pp. 759 - 766, http://dx.doi.org/10.1109/IROS.2016.7759137

Cruz F; Parisi GI; Wermter S, 2016, 'Learning contextual affordances with an associative neural architecture', in ESANN 2016 - 24th European Symposium on Artificial Neural Networks, pp. 665 - 670

Cruz F; Twiefel J; Magg S; Weber C; Wermter S, 2015, 'Interactive reinforcement learning through speech guidance in a domestic scenario', in Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN.2015.7280477

Cruz F; Magg S; Weber C; Wermter S, 2014, 'Improving reinforcement learning with interactive feedback and affordances', in IEEE ICDL-EPIROB 2014 - 4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, pp. 165 - 170, http://dx.doi.org/10.1109/DEVLRN.2014.6982975

Naranjo FC; Leiva GA, 2010, 'Indirect training with error backpropagation in gray-box neural model: Application to a chemical process', in Proceedings - International Conference of the Chilean Computer Science Society, SCCC, pp. 265 - 269, http://dx.doi.org/10.1109/SCCC.2010.41

Cruz F; Acuña G; Cubillos F; Moreno V; Bassi D, 2007, 'Indirect training of grey-box models: application to a bioprocess', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 391 - 397, http://dx.doi.org/10.1007/978-3-540-72393-6_47

Back to profile page