Select Publications
Book Chapters
2025, 'Boosting Reinforcement Learning Algorithms in Continuous Robotic Reaching Tasks Using Adaptive Potential Functions', in , pp. 52 - 64, http://dx.doi.org/10.1007/978-981-96-0351-0_5
,2019, 'Memory-Based Explainable Reinforcement Learning', in , pp. 66 - 77, http://dx.doi.org/10.1007/978-3-030-35288-2_6
,Journal articles
2024, 'UAV control in autonomous object-goal navigation: a systematic literature review', Artificial Intelligence Review, 57, http://dx.doi.org/10.1007/s10462-024-10758-7
,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
,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
,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
,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
,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
,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
,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
,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
,2023, 'Vessel Velocity Estimation and Docking Analysis: A Computer Vision Approach', Algorithms, 16, http://dx.doi.org/10.3390/a16070326
,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
,2023, 'Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments', Sensors, 23, http://dx.doi.org/10.3390/s23052681
,2023, 'Editorial: Cognitive inspired aspects of robot learning', Frontiers in Neurorobotics, 17, http://dx.doi.org/10.3389/fnbot.2023.1256788
,2022, 'Event-Based Angular Speed Measurement and Movement Monitoring', Sensors, 22, http://dx.doi.org/10.3390/s22207963
,2022, 'Analysis of Explainable Goal-Driven Reinforcement Learning in a Continuous Simulated Environment', Algorithms, 15, http://dx.doi.org/10.3390/a15030091
,2022, 'Convolution Optimization in Fire Classification', IEEE Access, 10, pp. 23642 - 23658, http://dx.doi.org/10.1109/ACCESS.2022.3151660
,2021, 'Diabetic retinopathy improved detection using deep learning', Applied Sciences (Switzerland), 11, http://dx.doi.org/10.3390/app112411970
,2021, 'Levels of explainable artificial intelligence for human-aligned conversational explanations', Artificial Intelligence, 299, http://dx.doi.org/10.1016/j.artint.2021.103525
,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
,2021, 'An evaluation methodology for interactive reinforcement learning with simulated users', Biomimetics, 6, pp. 1 - 15, http://dx.doi.org/10.3390/biomimetics6010013
,2020, 'Unmanned aerial vehicle control through domain-based automatic speech recognition', Computers, 9, pp. 1 - 15, http://dx.doi.org/10.3390/computers9030075
,2020, 'Deep reinforcement learning with interactive feedback in a human-robot environment', Applied Sciences (Switzerland), 10, http://dx.doi.org/10.3390/app10165574
,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
,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
,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
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
,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
,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
,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
,2023, 'Self context-aware emotion perception on human-robot interaction', in Australasian Conference on Robotics and Automation, ACRA
,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
,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
,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
,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
,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
,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
,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
,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
,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
,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
,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
,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
,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
,2019, 'Reinforcement learning using continuous states and interactive feedback', in ACM International Conference Proceeding Series, http://dx.doi.org/10.1145/3309772.3309801
,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
,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
,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
,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
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