ORCID as entered in ROS

Select Publications
Xie S; Meng Z; Bamdad M; Cruz F, 2024, 'Contextual Recognition Network: Combining DDPG and Contextual Affordances for Robotic Safe Grasping', in UbiComp Companion 2024 - Companion of the 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 41 - 45, http://dx.doi.org/10.1145/3675094.3677581
Darejeh A, 2024, 'A User-Centric Exploration of Axiomatic Explainable AI in Participatory Budgeting', Melbourne, Australia, presented at ACM UbiComp / ISWC 2024, Melbourne, Australia, 19 September 2024
Shang Y; Chen Y; Cruz F, 2024, 'Improving Proximal Policy Optimization Algorithm in Interactive Multi-Agent Systems', in 2024 IEEE International Conference on Development and Learning, ICDL 2024, http://dx.doi.org/10.1109/ICDL61372.2024.10644943
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
Acuña G; Cruz F; Moreno V, 2006, 'Identifiability of time varying parameters in a Grey-Box Neural Model: Application to a biotechnological process', in 4th International Conference on Simulation and Modelling in the Food and Bio-Industry 2006, FOODSIM 2006, pp. 26 - 31