Mitterauer, Bernhard J Outline of a Brain Model for Self-Observing Agents Journal Article Journal of Artificial Intelligence and Consciousness, 8 (1), pp. 2150008, 2021, ISSN: 2705-0785. Aguado, Esther; Milosevic, Zorana; Hernández, Carlos; Sanz, Ricardo; Garzon, Mario; Bozhinoski, Darko; Rossi, Claudio Functional self-awareness and metacontrol for underwater robot autonomy Journal Article Sensors (Switzerland), 21 (4), pp. 1–28, 2021, ISSN: 14248220. Pignaton de Freitas, Edison ; Olszewska, Joanna Isabelle; Carbonera, Joel Luís; Fiorini, Sandro R; Khamis, Alaa; Ragavan, Veera S; Barreto, Marcos E; Prestes, Edson; Habib, Maki K; Redfield, Signe; Chibani, Abdelghani; Goncalves, Paulo; Bermejo-Alonso, Julita; Sanz, Ricardo; Tosello, Elisa; Olivares-Alarcos, Alberto; Konzen, Andrea Aparecida; ã, Jo; Li, Howard Ontological concepts for information sharing in cloud robotics Journal Article Journal of Ambient Intelligence and Humanized Computing, 2020, ISSN: 18685145. Sanz, Ricardo; Aguado, Esther Understanding and Machine Consciousness Journal Article Journal of Artificial Intelligence and Consciousness, pp. 1–14, 2020, ISBN: 2705-0785. Sanz, R; Bermejo-Alonso, J; Rossi, C; Hernando, M; Irusta, K; Aguado, E An Apology for the “Self” Concept in Autonomous Robot Ontologies Book 2020, ISSN: 21945365. Sanz, Ricardo; Bermejo-Alonso, Julita; Rossi, Claudio; Hernando, Miguel; Irusta, Koro; Aguado, Esther Apologia for the ``Self'' Concept in Autonomous Robot Ontologies Inproceedings Proceedings of ROBOT'2019: Fourth Iberian Robotics Conference, Porto, Portugal, 2019. Diez-Olivan, Alberto; Pagan, Jose A; Sanz, Ricardo; Sierra, Basilio Deep evolutionary modeling of condition monitoring data in marine propulsion systems Journal Article Soft Computing, 23 (20), pp. 9937–9953, 2019, ISSN: 1433-7479. Diez-Olivan, A; Pagan, J A; Sanz, R; Sierra, B Deep evolutionary modeling of condition monitoring data in marine propulsion systems Journal Article Soft Computing, 23 (20), 2019, ISSN: 14337479. Janiesch, Christian; Fischer, Marcus; Winkelmann, Axel; Nentwich, Valentin Specifying autonomy in the Internet of Things: the autonomy model and notation Book Springer Berlin Heidelberg, 2019, ISSN: 16179854. Sanz, Ricardo Consciousness, Engineering, and Anthropomorphism Journal Article APA Newsletter on Philosophy and Computers, 19 (1), pp. 12–18, 2019. Diez-Olivan, A; Averós, X; Sanz, R; Sierra, B; Estevez, I Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming Journal Article Computers and Electronics in Agriculture, 161 , 2019, ISSN: 01681699. Sanz, Ricardo; Bermejo-Alonso, Julita Consciousness and Understanding in Autonomous Systems Inproceedings Chella, Antonio; Gamez, David; Lincoln, Patrick; Manzotti, Riccardo; Pfautz, Jonathan (Ed.): Proceedings of the 2019 Towards Conscious AI Systems Symposium. AAAI Spring Symposium Series (AAAI SSS-19), Palo Alto, CA, 2019. Sanz, Ricardo Sharing Knowledge in the Intelligent Robot Life-cycle Miscellaneous WOSRA IROS 2018 Workshop on Collaboratively Working towards Ontology-based Standards for Robotics and Automation, 2018. Diez-Olivan, Alberto; Pagan, Jose A; Khoa, Nguyen Lu Dang; Sanz, Ricardo; Sierra, Basilio Kernel-based support vector machines for automated health status assessment in monitoring sensor data Journal Article The International Journal of Advanced Manufacturing Technology, 95 (1-4), pp. 327–340, 2018, ISSN: 1433-3015. Kralik, Jerald D; Lee, Jee Hang; Rosenbloom, Paul S; Jackson, Philip C; Epstein, Susan L; Romero, Oscar J; Sanz, Ricardo; Larue, Othalia; Schmidtke, Hedda R; Lee, Sang Wan; McGreggor, Keith Metacognition for a Common Model of Cognition Inproceedings Procedia Computer Science, pp. 730–739, 2018, ISSN: 18770509. Diez Oliván, Alberto ; Averós, Xavier; Sanz, Ricardo; Sierra, Basilio; Estevez, Inma Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming Journal Article Computers and Electronics in Agriculture, 141-150 , 2018. Sanz, R; Bermejo-Alonso, J Consciousness and understanding in autonomous systems Inproceedings CEUR Workshop Proceedings, 2018, ISSN: 16130073. Hernández, C; Bermejo-Alonso, J; Sanz, R A self-adaptation framework based on functional knowledge for augmented autonomy in robots Journal Article Integrated Computer-Aided Engineering, 25 (2), 2018, ISSN: 18758835. Bermejo-Alonso, Julita; Salvador, Jorge; Sanz, Ricardo Towards an Ontology for Task and Planning in Autonomous Systems: An Emergency Scenario Incollection Ollero, Anibal; Sanfeliu, Alberto; Montano, Luis; Lau, Nuno; Cardeira, Carlos (Ed.): ROBOT 2017: Third Iberian Robotics Conference: Volume 1, pp. 429–440, Springer International Publishing, 2018, ISBN: 978-3-319-70833-1. Hernández, Carlos; Bermejo-Alonso, Julita; Sanz, Ricardo A self-adaptation framework based on functional knowledge for augmented autonomy in robots Journal Article Integrated Computer-Aided Engineering, 25 , pp. 157–172, 2018. Diez-Olivan, A; Pagan, J A; Khoa, N L D; Sanz, R; Sierra, B Kernel-based support vector machines for automated health status assessment in monitoring sensor data Journal Article International Journal of Advanced Manufacturing Technology, 95 (1-4), 2018, ISSN: 14333015. Bermejo-Alonso, J; Salvador, J; Sanz, R Towards an ontology for task and planning in autonomous systems: An emergency scenario Book 2018, ISSN: 21945357. Bermejo-Alonso, Julita; Sanz, Ricardo Towards an Ontology for Task and Planning in Autonomous Systems: a Case Study for an Emergency Scenario Inproceedings ROBOT'2017 - Third Iberian Robotics Conference, Seville, Spain, 2017. Rodr$backslash$'$backslash$iguez, Manuel; D$backslash$'$backslash$iaz, Ismael; Bermejo, Julia; Sanz, Ricardo; Hernández, Carlos Integral Management of Process Plants Systems through their Lifecycle using a Model-Based Engineering Approach Inproceedings ñ, Antonio Espu; Graells, Moises; Puigjaner, Luis (Ed.): Proceedings of the 27th European Symposium on Computer Aided Process Engineering -- ESCAPE 27, Barcelona, Spain, 2017. Cabre, Jesus Alejandro Cárdenes; Precup, Doina; Sanz, Ricardo Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation Inproceedings 2017 International Conference on Cloud and Autonomic Computing (ICCAC), pp. 184–185, 2017. Díez-Olivan, Alberto; Pagan, Jose A; Sanz, Ricardo; Sierra, Basilio Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score Journal Article Neurocomputing, 241 , pp. 97–107, 2017, ISBN: 0925-2312. Olszewska, Joanna Isabelle; Barreto, Marcos E; Bermejo-Alonso, Julita; Carbonera, Joel Luis; Chibani, Abdelghani; Fiorini, Sandro Rama; ç, Paulo Jorge Sequeira Gon; Habib, Maki K; Khamis, Alaa; Alarcos, Alberto Olivares; de Freitas, Edison Pignaton; Prestes, Edson; Ragavan, Veera S; Redfield, Signe; Sanz, Ricardo; Spencer, Bruce; Li, Howard Ontology for autonomous robotics Inproceedings Proceedings of 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 189–194, IEEE, 2017, ISBN: 978-1-5386-3518-6. Diez-Olivan, A; Penalva, M; Veiga, F; Deitert, L; Sanz, R; Sierra, B Kernel density-based pattern classification in blind fasteners installation Book 2017, ISSN: 16113349. Sanz, Ricardo; Bermejo, Julita; Morago, Juan; Hernández, Carlos Ontologies as Backbone of Cognitive Systems Engineering Inproceedings Proceedings of AISB CAOS 2017: Cognition And OntologieS, Bath, UK, 2017. Diez-Olivan, A; Pagan, J A; Sanz, R; Sierra, B Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score Journal Article Neurocomputing, 241 , 2017, ISSN: 18728286. Cabré, J A C; Precup, D; Sanz, R Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation Inproceedings Proceedings - 2017 IEEE International Conference on Cloud and Autonomic Computing, ICCAC 2017, 2017, ISBN: 9781538619391. Diez-Olivan, Alberto; Penalva, Mariluz; Veiga, Fernando; Deitert, Lutz; Sanz, Ricardo; Sierra, Basilio Kernel Density-Based Pattern Classification in Blind Fasteners Installation Incollection de Pisón, Francisco Javier Mart$backslash$'$backslash$inez; Urraca, Rubén; Quintián, Héctor; Corchado, Emilio (Ed.): Hybrid Artificial Intelligence Systems HAIS 2017, 10334 , pp. 195–206, Springer International Publishing, 2017. Rodriguez, M; Díaz, I; Bermejo, J; Sanz, R; Hernández, C 2017, ISSN: 15707946. Olszewska, Joanna Isabelle; Barreto, Marcos; Bermejo-Alonso, Julita; Carbonera, Joel; Chibani, Abdelghani; Fiorini, Sandro; Goncalves, Paulo; Habib, Maki; Khamis, Alaa; Olivares, Alberto; De Freitas, Edison Pignaton ; Prestes, Edson; Ragavan, Veera S; Redfield, Signe; Sanz, Ricardo; Spencer, Bruce; Li, Howard Ontology for autonomous robotics Inproceedings RO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication, pp. 189–194, Lisbon, Portugal, 2017, ISBN: 9781538635186. Hernández, Carlos; Rodr$backslash$'$backslash$iguez, Manuel; D$backslash$'$backslash$iaz, Ismael; Sanz, Ricardo Model-Based Engineering of Process Plants Using SysML Inproceedings Proceedings of the 26th European Symposium on Computer Aided Process Engineering, ESCAPE 26, pp. 1281–1286, Portorož, Slovenia, 2016. Bermejo-Alonso, J; Hernandez, C; Sanz, R Model-based engineering of autonomous systems using ontologies and metamodels Inproceedings ISSE 2016 - 2016 International Symposium on Systems Engineering - Proceedings Papers, 2016, ISBN: 9781509007936. Herrera, Carlos; Sanz, Ricardo Heideggerian AI and the Being of Robots Book Chapter Müller, Vincent C (Ed.): Fundamental Issues of Artificial Intelligence, pp. 497–513, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-26485-1. Herrera, Carlos; Sanz, Ricardo Heideggerian AI and the being of robots Incollection Müller, Vincent C (Ed.): Fundamental Issues of Artificial Intelligence, (377), Springer, 2016. Bermejo-Alonso, Julia; Hernández, Carlos; Sanz, Ricardo Model-based Engineering of Autonomous Systems using Ontologies and Metamodels Inproceedings IEEE International Symposium on Systems Engineering 2016 (IEEE ISSE 2016), Edinburgh, Scotland, 2016. Hernandez, C; Rodriguez, M; Diaz, I; Sanz, R Model Based Engineering of Process Plants using SysML Book 2016, ISSN: 15707946. Bayat, Behzad; Bermejo-Alonso, Julita; Carbonera, Joel; Facchinetti, Tullio; Fiorini, Sandro; Goncalves, Paulo; Jorge, Vitor A M; Habib, Maki; Khamis, Alaa; Melo, Kamilo; Nguyen, Bao; Olszewska, Joanna Isabelle; Paull, Liam; Prestes, Edson; Ragavan, Veera; Saeedi, Sajad; Sanz, Ricardo; Seto, Mae; Spencer, Bruce; Vosughi, Amirkhosro; Li, Howard Requirements for building an ontology for autonomous robots Journal Article Industrial Robot: An International Journal, 43 (5), pp. 469–480, 2016, ISBN: 0143-991X. Hernández, Carlos; Fernández, José L; Sánchez-Escribano, Guadalupe; Bermejo-Alonso, Julita; Sanz, Ricardo Model-Based Metacontrol for Self-adaptation Inproceedings Liu, Honghai; Kubota, Naoyuki; Zhu, Xiangyang; Dillmann, Rüdiger; Zhou, Dalin (Ed.): Proceedings of the 8th International Conference on Intelligent Robotics and Applications, ICIRA 2015, pp. 643–654, Springer, Portsmouth, 2015. Sánchez-Escribano, M G; Herrera, C; Sanz, R The Exploitation of Models in Artificial Emotions Incollection Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics, pp. 154–169, IGI Global, 2015. Hernández, C; Fernández, J L; Sánchez-Escribano, G; Bermejo-Alonso, J; Sanz, R Model-based metacontrol for self-adaptation Book 2015, ISSN: 16113349. Diez, Alberto; Pagán, José A; Sanz, Ricardo A Methodology for Predicting Abnormal Behaviors in Vessel Engines Inproceedings 2014 International Conference on Artificial Intelligence (ICOAI 2014), Barcelona, Spain, 2014. Sanz, Ricardo; Hernandez, Carlos; Rodriguez, Manuel; Bermejo, Julita; Lopez, Ignacio Improved Resilience Controllers Using Cognitive Patterns Inproceedings Proceedings of 19th IFAC World Congress, pp. 683–688, Cape Town, South Africa, 2014. Nivel, Eric; Thórisson, Kristinn R; Steunebrink, Bas R; Dindo, Haris; Pezzulo, Giovanni; Rodriguez, Manuel; Hernandez, Carlos; Ognibene, Dimitri; Schmidhuber, Jürgen; Sanz, Ricardo; Helgason, Helgi P; Chella, Antonio; Jonsson, Gudberg K Autonomous Acquisition of Natural Language Inproceedings Proceedings of IADIS International Conference on Intelligent Systems $backslash$& Agents 2014 (ISA-14), pp. 58–66, Lisbon, Portugal, 2014. Ródenas, Luis; Sanz, Ricardo; Albiol, Pablo; Castillo, Alberto; ú, Daniel Verd; Garc$backslash$'$backslash$ia, Pedro Plataforma para la implementación y validación de algoritmos de control de tiempo real en mini-helicópteros de varios rotores Inproceedings Jornadas de Automática, Valencia, Spain, 2014. Nivel, Eric; Thórisson, Kristinn R; Steunebrink, Bas R; Dindo, Haris; Pezzulo, Giovanni; Rodríguez, Manuel; Hernández, Carlos; Ognibene, Dimitri; Schmidhuber, Jürgen; Sanz, Ricardo; Helgason, Helgi P; Chella, Antonio Bounded seed-AGI Inproceedings International Conference on Artificial General Intelligence - AGI 2014, pp. 85–96, 2014, ISSN: 16113349. Herrera, Carlos; Sánchez-Escribano, María Guadalupe; Sanz, Ricardo The embodiment of synthetic emotion Incollection Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics, pp. 204–212, 2014, ISBN: 9781466672796.
2021
title = {Outline of a Brain Model for Self-Observing Agents},
author = {Bernhard J Mitterauer},
doi = {10.1142/s2705078521500089},
issn = {2705-0785},
year = {2021},
date = {2021-01-01},
journal = {Journal of Artificial Intelligence and Consciousness},
volume = {8},
number = {1},
pages = {2150008},
abstract = {Brain-inspired models for conscious robots should refer to the cellular double structure of the brain, consisting of the neuronal system and the glial system, embodying two ontological realms. Therefore, a purely neurobiological approach to machine consciousness is biased by an ontological fault in exclusively referring to the neuronal system. The brain model for self-observing agents outlined in this paper focuses on the glial-neuronal synaptic units (tripartite synapses). Whereas the neuronal component of the synapse embodies objective subjectivity processing sensory information, the glial component (astrocyte) embodies subjective subjectivity generating subjective behavior (intentions, consciousness) in its interactions with the neuronal part of the synapse. The elementary principle of the implementation of self-observing agents is this: a brain is capable of self-observation, if the concept of intention to observe something and the concept of the observed are located in different places. Based on a formalism of qualitative information processing, the architecture of self-observation is described in increasing complexity, building networks. It is suggested that if a robot brain is equipped with a network of modules for self-observation, the robot may generate subjective perspectives of self-observation indicating self-consciousness.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Functional self-awareness and metacontrol for underwater robot autonomy},
author = {Esther Aguado and Zorana Milosevic and Carlos Hernández and Ricardo Sanz and Mario Garzon and Darko Bozhinoski and Claudio Rossi},
doi = {10.3390/s21041210},
issn = {14248220},
year = {2021},
date = {2021-01-01},
journal = {Sensors (Switzerland)},
volume = {21},
number = {4},
pages = {1--28},
abstract = {Autonomous systems are expected to maintain a dependable operation without human intervention. They are intended to fulfill the mission for which they were deployed, properly handling the disturbances that may affect them. Underwater robots, such as the UX-1 mine explorer developed in the UNEXMIN project, are paradigmatic examples of this need. Underwater robots are affected by both external and internal disturbances that hamper their capability for autonomous operation. Long-term autonomy requires not only the capability of perceiving and properly acting in open environments but also a sufficient degree of robustness and resilience so as to maintain and recover the operational functionality of the system when disturbed by unexpected events. In this article, we analyze the operational conditions for autonomous underwater robots with a special emphasis on the UX-1 miner explorer. We then describe a knowledge-based self-awareness and metacontrol subsystem that enables the autonomous reconfiguration of the robot subsystems to keep mission-oriented capability. This resilience augmenting solution is based on the deep modeling of the functional architecture of the autonomous robot in combination with ontological reasoning to allow self-diagnosis and reconfiguration during operation. This mechanism can transparently use robot functional redundancy to ensure mission satisfaction, even in the presence of faults.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
title = {Ontological concepts for information sharing in cloud robotics},
author = {Edison {Pignaton de Freitas} and Joanna Isabelle Olszewska and Joel Luís Carbonera and Sandro R Fiorini and Alaa Khamis and Veera S Ragavan and Marcos E Barreto and Edson Prestes and Maki K Habib and Signe Redfield and Abdelghani Chibani and Paulo Goncalves and Julita Bermejo-Alonso and Ricardo Sanz and Elisa Tosello and Alberto Olivares-Alarcos and Andrea Aparecida Konzen and Jo{ã}o Quintas and Howard Li},
doi = {10.1007/s12652-020-02150-4},
issn = {18685145},
year = {2020},
date = {2020-01-01},
journal = {Journal of Ambient Intelligence and Humanized Computing},
abstract = {Recent research and developments in cloud robotics (CR) require appropriate knowledge representation to ensure interoperable data, information, and knowledge sharing within cloud infrastructures. As an important branch of the Internet of Things (IoT), these demands to advance it forward motivates academic and industrial sectors to invest on it. The IEEE 'Ontologies for Robotics and Automation' Working Group (ORA WG) has been developing standard ontologies for different robotic domains, including industrial and autonomous robots. The use of such robotic standards has the potential to benefit the Cloud Robotic Community (CRC) as well, supporting the provision of ubiquitous intelligent services by the CR-based systems. This paper explores this potential by developing an ontological approach for effective information sharing in cloud robotics scenarios. It presents an extension to the existing ontological standards to cater for the CR domain. The use of the new ontological elements is illustrated through its use in a couple of CR case studies. To the best of our knowledge, this is the first work ever that implements an ontology comprising concepts and axioms applicable to the CR domain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Understanding and Machine Consciousness},
author = {Ricardo Sanz and Esther Aguado},
isbn = {2705-0785},
year = {2020},
date = {2020-01-01},
journal = {Journal of Artificial Intelligence and Consciousness},
pages = {1--14},
publisher = {World Scientific Publishing Co.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {An Apology for the “Self” Concept in Autonomous Robot Ontologies},
author = {R Sanz and J Bermejo-Alonso and C Rossi and M Hernando and K Irusta and E Aguado},
doi = {10.1007/978-3-030-35990-4_34},
issn = {21945365},
year = {2020},
date = {2020-01-01},
booktitle = {Advances in Intelligent Systems and Computing},
volume = {1092 AISC},
abstract = {This paper focuses on the core idea that underlies all mechanisms for system self-awareness: “Self”. Robot self awareness is a hot topic not only from a bioinspiration perspective but also from a more profound reflection-based strategy for increased autonomy and resilience. In this paper we address the uses and genealogy of the concept of “self”, its value in the implementation of robots and the role it may play in autonomous robotic systems' architectures. We hence propose the inclusion of the “Self” concept in the future IEEE AuR standard ontology.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
2019
title = {Apologia for the ``Self'' Concept in Autonomous Robot Ontologies},
author = {Ricardo Sanz and Julita Bermejo-Alonso and Claudio Rossi and Miguel Hernando and Koro Irusta and Esther Aguado},
year = {2019},
date = {2019-11-01},
booktitle = {Proceedings of ROBOT'2019: Fourth Iberian Robotics Conference},
address = {Porto, Portugal},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Deep evolutionary modeling of condition monitoring data in marine propulsion systems},
author = {Alberto Diez-Olivan and Jose A Pagan and Ricardo Sanz and Basilio Sierra},
issn = {1433-7479},
year = {2019},
date = {2019-10-01},
journal = {Soft Computing},
volume = {23},
number = {20},
pages = {9937--9953},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Deep evolutionary modeling of condition monitoring data in marine propulsion systems},
author = {A Diez-Olivan and J A Pagan and R Sanz and B Sierra},
doi = {10.1007/s00500-018-3549-3},
issn = {14337479},
year = {2019},
date = {2019-01-01},
journal = {Soft Computing},
volume = {23},
number = {20},
abstract = {In many complex industrial scenarios where condition monitoring data are involved, data-driven models can highly support maintenance tasks and improve assets' performance. To infer physical meaningful models that accurately characterize assets' behaviors across a wide range of operating conditions is a difficult issue. Usually, data-driven models are in black-box format, accurate but too complex to intelligibly explain the inherent physics of the process and lacking in conciseness. This study presents a deep evolutionary-based approach to optimally model and predict physical behaviors in industrial assets from operational data. The evolutionary modeling process is combined with long short-term memory networks, which are trained on estimations made by the evolutionary physical model and then used to predict sequences of data over a number of time steps. The likelihood of behaviors of interest is assessed by means of the resulting sequences of residuals, and a resulting score is computed over time. The proposed approach is applied to model and predict a set of temperatures related to a marine propulsion system, anticipating anomalies and changes in operating conditions. It is demonstrated that deep evolutionary modeling results are quite satisfactory for prognostics and obtained physical models are practical and easy to understand.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Specifying autonomy in the Internet of Things: the autonomy model and notation},
author = {Christian Janiesch and Marcus Fischer and Axel Winkelmann and Valentin Nentwich},
url = {https://doi.org/10.1007/s10257-018-0379-x},
doi = {10.1007/s10257-018-0379-x},
issn = {16179854},
year = {2019},
date = {2019-01-01},
booktitle = {Information Systems and e-Business Management},
volume = {17},
number = {1},
pages = {159--194},
publisher = {Springer Berlin Heidelberg},
abstract = {Driven by digitization in society and industry, automating behavior in an autonomous way substantially alters industrial value chains in the smart service world. As processes are enhanced with sensor and actuator technology, they become digitally interconnected and merge into an Internet of Things (IoT) to form cyber-physical systems. Using these automated systems, enterprises can improve the performance and quality of their operations. However, currently it is neither feasible nor reasonable to equip any machine with full autonomy when networking with other machines or people. It is necessary to specify rules for machine behavior that also determine an adequate degree of autonomy to realize the potential benefits of the IoT. Yet, there is a lack of methodologies and guidelines to support the design and implementation of machines as explicit autonomous agents such that many designs only consider autonomy implicitly. To address this research gap, we perform a comprehensive literature review to extract 12 requirements for the design of autonomous agents in the IoT. We introduce a set of constitutive characteristics for agents and introduce a classification framework for interactions in multi-agent systems. We integrate our findings by developing a conceptual modeling language consisting of a meta model and a notation that facilitates the specification and design of autonomous agents within the IoT as well as CPS: the autonomy model and notation. We illustrate and discuss the approach and its limitations.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
title = {Consciousness, Engineering, and Anthropomorphism},
author = {Ricardo Sanz},
year = {2019},
date = {2019-01-01},
journal = {APA Newsletter on Philosophy and Computers},
volume = {19},
number = {1},
pages = {12--18},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming},
author = {A Diez-Olivan and X Averós and R Sanz and B Sierra and I Estevez},
doi = {10.1016/j.compag.2018.03.025},
issn = {01681699},
year = {2019},
date = {2019-01-01},
journal = {Computers and Electronics in Agriculture},
volume = {161},
abstract = {An efficient and sustainable animal production requires fine-tuning and control of all the parameters involved. But this is not a simple task. Animal farming is a complex biological system in which environmental parameters and management practices interact in a dynamic way. In addition, the typical non-linear response of biological processes implies that relationships across parameters that are critical to assure animal welfare and performance are difficult to determine. In this paper a novel decision support system based on environmental indicators and on weights, leg problems and mortality rates is proposed to address this issue. The data-driven modeling process is performed by a quantile regression forests approach that allows estimating growth, welfare and mortality parameters on the basis of environmental deviations from optimal farm conditions. Resulting models also provide confidence intervals able to deal with uncertainty. They are deployed in farm, offering an accessible tool for farmers, veterinarians and technical personnel. Experimental results involving 20 flocks of broiler meat chickens from different farms show the validity of the system, obtaining robust prediction intervals and high accuracy, namely over 81% for every model. The in-field use of the proposed approach will facilitate an efficient and animal welfare-friendly production management.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Consciousness and Understanding in Autonomous Systems},
author = {Ricardo Sanz and Julita Bermejo-Alonso},
editor = {Antonio Chella and David Gamez and Patrick Lincoln and Riccardo Manzotti and Jonathan Pfautz},
year = {2019},
date = {2019-01-01},
booktitle = {Proceedings of the 2019 Towards Conscious AI Systems Symposium. AAAI Spring Symposium Series (AAAI SSS-19)},
address = {Palo Alto, CA},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2018
title = {Sharing Knowledge in the Intelligent Robot Life-cycle},
author = {Ricardo Sanz},
year = {2018},
date = {2018-10-01},
howpublished = {WOSRA IROS 2018 Workshop on Collaboratively Working towards Ontology-based Standards for Robotics and Automation},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
title = {Kernel-based support vector machines for automated health status assessment in monitoring sensor data},
author = {Alberto Diez-Olivan and Jose A Pagan and Nguyen Lu Dang Khoa and Ricardo Sanz and Basilio Sierra},
issn = {1433-3015},
year = {2018},
date = {2018-03-01},
journal = {The International Journal of Advanced Manufacturing Technology},
volume = {95},
number = {1-4},
pages = {327--340},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Metacognition for a Common Model of Cognition},
author = {Jerald D Kralik and Jee Hang Lee and Paul S Rosenbloom and Philip C Jackson and Susan L Epstein and Oscar J Romero and Ricardo Sanz and Othalia Larue and Hedda R Schmidtke and Sang Wan Lee and Keith McGreggor},
doi = {10.1016/j.procs.2018.11.046},
issn = {18770509},
year = {2018},
date = {2018-01-01},
booktitle = {Procedia Computer Science},
volume = {145},
pages = {730--739},
abstract = {This paper provides a starting point for the development of metacognition in a common model of cognition. It identifies significant theoretical work on metacognition from multiple disciplines that the authors believe worthy of consideration. After first defining cognition and metacognition, we outline three general categories of metacognition, provide an initial list of its main components, consider the more difficult problem of consciousness, and present examples of prominent artificial systems that have implemented metacognitive components. Finally, we identify pressing design issues for the future.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming},
author = {Alberto {Diez Oliván} and Xavier Averós and Ricardo Sanz and Basilio Sierra and Inma Estevez},
year = {2018},
date = {2018-01-01},
journal = {Computers and Electronics in Agriculture},
volume = {141-150},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Consciousness and understanding in autonomous systems},
author = {R Sanz and J Bermejo-Alonso},
issn = {16130073},
year = {2018},
date = {2018-01-01},
booktitle = {CEUR Workshop Proceedings},
volume = {2287},
abstract = {This position paper will highlight the importance of having a formal notion of understanding as one of the cornerstones in the construction of conscious AIs. It will show that the capability of understanding both the perceptual and the action flows is critical for the correct operation of situated autonomous systems. An assessment is also made on the contribution of the machine learning domain towards this direction.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {A self-adaptation framework based on functional knowledge for augmented autonomy in robots},
author = {C Hernández and J Bermejo-Alonso and R Sanz},
doi = {10.3233/ICA-180565},
issn = {18758835},
year = {2018},
date = {2018-01-01},
journal = {Integrated Computer-Aided Engineering},
volume = {25},
number = {2},
abstract = {Robot control software endows robots with advanced capabilities for autonomous operation, such as navigation, object recognition or manipulation, in unstructured and dynamic environments. However, there is a steady need for more robust operation, where robots should perform complex tasks by reliably exploiting these novel capabilities. Mission-level resilience is required in the presence of component faults through failure recovery. To address this challenge, a novel self-adaptation framework based on functional knowledge for augmented autonomy is presented. A metacontroller is integrated on top of the robot control system, and it uses an explicit run-time model of the robot's controller and its mission to adapt to operational changes. The model is grounded on a functional ontology that relates the robot's mission with the robot's architecture, and it is generated during the robot's development from its engineering models. Advantages are discussed from both theoretical and practical viewpoints. An application example in a real autonomous mobile robot is provided. In this example, the generic metacontroller uses the robot's functional model to adapt the control architecture to recover from a sensor failure.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Towards an Ontology for Task and Planning in Autonomous Systems: An Emergency Scenario},
author = {Julita Bermejo-Alonso and Jorge Salvador and Ricardo Sanz},
editor = {Anibal Ollero and Alberto Sanfeliu and Luis Montano and Nuno Lau and Carlos Cardeira},
isbn = {978-3-319-70833-1},
year = {2018},
date = {2018-01-01},
booktitle = {ROBOT 2017: Third Iberian Robotics Conference: Volume 1},
pages = {429--440},
publisher = {Springer International Publishing},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
title = {A self-adaptation framework based on functional knowledge for augmented autonomy in robots},
author = {Carlos Hernández and Julita Bermejo-Alonso and Ricardo Sanz},
year = {2018},
date = {2018-01-01},
journal = {Integrated Computer-Aided Engineering},
volume = {25},
pages = {157--172},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Kernel-based support vector machines for automated health status assessment in monitoring sensor data},
author = {A Diez-Olivan and J A Pagan and N L D Khoa and R Sanz and B Sierra},
doi = {10.1007/s00170-017-1204-2},
issn = {14333015},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Advanced Manufacturing Technology},
volume = {95},
number = {1-4},
abstract = {This paper presents a novel algorithm to assess the health status in monitoring sensor data using a kernel-based support vector machine (SVM) approach. Today, accurate fault prediction is a key issue raised by maintenance. In particular, automatically modelling the normal behaviour from condition monitoring data is probably one of the most challenging problems, specially when there is limited information of real faults. To overcome this difficulty, a data-driven learning framework based on nonparametric density estimation for outlier detection and $nu$-SVM for normality modelling, with optimal bandwidth selection, is proposed. A health score based on the log-normalisation of the distance to the separating hyperplane is also provided. Experimental results obtained when analysing the propagation of a critical fault over time in a marine diesel engine demonstrate the validity of the algorithm. The predictions of normality models learned were compared to those of the k-nearest neighbours (kNN) method. Low false positive rates on healthy data and improved prediction capacities are achieved.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Towards an ontology for task and planning in autonomous systems: An emergency scenario},
author = {J Bermejo-Alonso and J Salvador and R Sanz},
doi = {10.1007/978-3-319-70833-1_35},
issn = {21945357},
year = {2018},
date = {2018-01-01},
booktitle = {Advances in Intelligent Systems and Computing},
volume = {693},
abstract = {Emergency scenarios where chemical explosions or fire outbreaks take place become dangerous environments to send a human team to. UAVs and UGVs working together with the human rescue team can prevent endangering the human team. To perform the emergency tasks, it is necessary to define what the UAV/UGV robotic system will do in the emergency area, detailing what each of the robots will specifically carry out. Next, the different actions should be planned to perform such tasks. An ontology–based approach is described in this paper, where the cohesive element to specify the planning process is a task ontology. We describe the initial contents of our ontology for task and planning in autonomous robots, with an example of its use within an emergency scenario where a combined UAV/UGV robotic system is supposed to act.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
2017
title = {Towards an Ontology for Task and Planning in Autonomous Systems: a Case Study for an Emergency Scenario},
author = {Julita Bermejo-Alonso and Ricardo Sanz},
year = {2017},
date = {2017-11-01},
booktitle = {ROBOT'2017 - Third Iberian Robotics Conference},
address = {Seville, Spain},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Integral Management of Process Plants Systems through their Lifecycle using a Model-Based Engineering Approach},
author = {Manuel Rodr$backslash$'$backslash$iguez and Ismael D$backslash$'$backslash$iaz and Julia Bermejo and Ricardo Sanz and Carlos Hernández},
editor = {Antonio Espu{ñ}a and Moises Graells and Luis Puigjaner},
year = {2017},
date = {2017-10-01},
booktitle = {Proceedings of the 27th European Symposium on Computer Aided Process Engineering -- ESCAPE 27},
address = {Barcelona, Spain},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation},
author = {Jesus Alejandro Cárdenes Cabre and Doina Precup and Ricardo Sanz},
year = {2017},
date = {2017-09-01},
booktitle = {2017 International Conference on Cloud and Autonomic Computing (ICCAC)},
pages = {184--185},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score},
author = {Alberto Díez-Olivan and Jose A Pagan and Ricardo Sanz and Basilio Sierra},
isbn = {0925-2312},
year = {2017},
date = {2017-06-01},
journal = {Neurocomputing},
volume = {241},
pages = {97--107},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Ontology for autonomous robotics},
author = {Joanna Isabelle Olszewska and Marcos E Barreto and Julita Bermejo-Alonso and Joel Luis Carbonera and Abdelghani Chibani and Sandro Rama Fiorini and Paulo Jorge Sequeira Gon{ç}alves and Maki K Habib and Alaa Khamis and Alberto Olivares Alarcos and Edison Pignaton de Freitas and Edson Prestes and Veera S Ragavan and Signe Redfield and Ricardo Sanz and Bruce Spencer and Howard Li},
isbn = {978-1-5386-3518-6},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)},
pages = {189--194},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Kernel density-based pattern classification in blind fasteners installation},
author = {A Diez-Olivan and M Penalva and F Veiga and L Deitert and R Sanz and B Sierra},
doi = {10.1007/978-3-319-59650-1_17},
issn = {16113349},
year = {2017},
date = {2017-01-01},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {10334 LNCS},
abstract = {In this work we introduce a kernel density-based pattern classification approach for the automatic identification of behavioral patterns from monitoring data related to blind fasteners installation. High density regions are estimated from feature space to establish behavioral patterns, automatically removing outliers and noisy instances in an iterative process. First the kernel density estimator is applied on the fastener features representing the quality of the installation. Then the behavioral patterns are identified from resulting high density regions, also considering the proximity between instances. Patterns are computed as the average of related monitoring torque-rotation diagrams. New fastening installations can be thus automatically classified in an online fashion. In order to show the validity of the approach, experiments have been conducted on real fastening data. Experimental results show an accurate pattern identification and classification approach, obtaining a global accuracy over 78% and improving current detection capabilities and existing evaluation systems.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
title = {Ontologies as Backbone of Cognitive Systems Engineering},
author = {Ricardo Sanz and Julita Bermejo and Juan Morago and Carlos Hernández},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of AISB CAOS 2017: Cognition And OntologieS},
address = {Bath, UK},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score},
author = {A Diez-Olivan and J A Pagan and R Sanz and B Sierra},
doi = {10.1016/j.neucom.2017.02.024},
issn = {18728286},
year = {2017},
date = {2017-01-01},
journal = {Neurocomputing},
volume = {241},
abstract = {Today, failure modes characterization and early detection is a key issue in complex assets. This is due to the negative impact of corrective operations and the conservative strategies usually put in practice, focused on preventive maintenance. In this paper anomaly detection issue is addressed in new monitoring sensor data by characterizing and modeling operational behaviors. The learning framework is performed on the basis of a machine learning approach that combines constrained K-means clustering for outlier detection and fuzzy modeling of distances to normality. A final score is also calculated over time, considering the membership degree to resulting fuzzy sets and a local outlier factor. Proposed solution is deployed in a CBM+ platform for online monitoring of the assets. In order to show the validity of the approach, experiments have been conducted on real operational faults in an auxiliary marine diesel engine. Experimental results show a fully comprehensive yet accurate prognostics approach, improving detection capabilities and knowledge management. The performance achieved is quite high (precision, sensitivity and specificity above 93% and $kappa$=0.93), even more so given that a very small percentage of real faults are present in data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation},
author = {J A C Cabré and D Precup and R Sanz},
doi = {10.1109/ICCAC.2017.25},
isbn = {9781538619391},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings - 2017 IEEE International Conference on Cloud and Autonomic Computing, ICCAC 2017},
abstract = {Over-booking or under-booking of computing resources leads to higher cost and performance degradation of web applications. To optimize the performance of web applications, access to the resources has to be dynamically controlled ensuring maximum cost-performance ratio of the application while fulfilling requirements. To simplify the design of dynamic cloud controllers, we propose a horizontal and vertical scalability self-aware agent defined by a self-adaptive fuzzy logic with an oriented random optimizer based on reward and memory. The algorithm dynamically adjusts the membership functions and their relationship, maximizing the reward of the system while considering the cost related to the deployment of new resources. The evaluation of the controller under real cloud workload reveals the ability of the algorithm to maximize the performance of the web application based on the target parameters given by an operator.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Kernel Density-Based Pattern Classification in Blind Fasteners Installation},
author = {Alberto Diez-Olivan and Mariluz Penalva and Fernando Veiga and Lutz Deitert and Ricardo Sanz and Basilio Sierra},
editor = {Francisco Javier Mart$backslash$'$backslash$inez de Pisón and Rubén Urraca and Héctor Quintián and Emilio Corchado},
year = {2017},
date = {2017-01-01},
booktitle = {Hybrid Artificial Intelligence Systems HAIS 2017},
volume = {10334},
pages = {195--206},
publisher = {Springer International Publishing},
series = {Lecture Notes in Artificial Intelligence},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
title = {Integral Management of Process Plants Systems through their Lifecycle using a Model-Based Engineering Approach},
author = {M Rodriguez and I Díaz and J Bermejo and R Sanz and C Hernández},
doi = {10.1016/B978-0-444-63965-3.50341-X},
issn = {15707946},
year = {2017},
date = {2017-01-01},
booktitle = {Computer Aided Chemical Engineering},
volume = {40},
abstract = {Nowadays we find ourselves in what is called the fourth industrial revolution: Industry 4.0. This revolution is being fostered in many countries to get a more competitive industry. Industry 4.0 target is to make more efficient and flexible plants, reduce times and costs of process and products lifecycle. Under this framework, models appear as a core component in every new development. Model-Based Systems Engineering is a methodology that allows for traceability and guarantees model consistency covering the entire lifecycle of the system. The objective of this work is to develop a holistic model of a process plant. Such model will be available during the entire lifecycle of the system (process + product) communicating in every stage with the specific (existing) tools used to develop it. In this paper, we present the development of the SysML model of a process plant (the production of ethylbenzene from benzene and ethylene), the architecture and the methodology to transform the central model to application-specific ones. We also explain how to execute these specific models from the core model keeping consistency between models and data.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
title = {Ontology for autonomous robotics},
author = {Joanna Isabelle Olszewska and Marcos Barreto and Julita Bermejo-Alonso and Joel Carbonera and Abdelghani Chibani and Sandro Fiorini and Paulo Goncalves and Maki Habib and Alaa Khamis and Alberto Olivares and Edison Pignaton {De Freitas} and Edson Prestes and Veera S Ragavan and Signe Redfield and Ricardo Sanz and Bruce Spencer and Howard Li},
doi = {10.1109/ROMAN.2017.8172300},
isbn = {9781538635186},
year = {2017},
date = {2017-01-01},
booktitle = {RO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication},
pages = {189--194},
address = {Lisbon, Portugal},
abstract = {Creating a standard for knowledge representation and reasoning in autonomous robotics is an urgent task if we consider recent advances in robotics as well as predictions about the insertion of robots in human daily life. Indeed, this will impact the way information is exchanged between multiple robots or between robots and humans and how they can all understand it without ambiguity. Indeed, Human Robot Interaction (HRI) represents the interaction of at least two cognition models (Human and Robot). Such interaction informs task composition, task assignment, communication, cooperation and coordination in a dynamic environment, requiring a flexible representation. Hence, this paper presents the IEEE RAS Autonomous Robotics (AuR) Study Group, which is a spin-off of the IEEE Ontologies for Robotics and Automation (ORA) Working Group, and and its ongoing work to develop the first IEEE-RAS ontology standard for autonomous robotics. In particular, this paper reports on the current version of the ontology for autonomous robotics as well as on its first implementation successfully validated for a human-robot interaction scenario, demonstrating the developed ontology's strengths which include semantic interoperability and capability to relate ontologies from different fields for knowledge sharing and interactions.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2016
title = {Model-Based Engineering of Process Plants Using SysML},
author = {Carlos Hernández and Manuel Rodr$backslash$'$backslash$iguez and Ismael D$backslash$'$backslash$iaz and Ricardo Sanz},
year = {2016},
date = {2016-06-01},
booktitle = {Proceedings of the 26th European Symposium on Computer Aided Process Engineering, ESCAPE 26},
pages = {1281--1286},
address = {Portorož, Slovenia},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Model-based engineering of autonomous systems using ontologies and metamodels},
author = {J Bermejo-Alonso and C Hernandez and R Sanz},
doi = {10.1109/SysEng.2016.7753185},
isbn = {9781509007936},
year = {2016},
date = {2016-01-01},
booktitle = {ISSE 2016 - 2016 International Symposium on Systems Engineering - Proceedings Papers},
abstract = {Our research focuses on engineering processes for autonomous intelligent systems construction with a life-cycle holistic view, by means of a model-based framework. The conceptual core of the framework is ontologically-driven. Our ontological approach consists of two elements. The first one is a domain Ontology for Autonomous Systems (OASys) to capture the autonomous system structure, function and behaviour. The second element is an Ontology-driven Engineering Methodology (ODEM) to develop the target autonomous system. This methodology is based on Model-based Systems Engineering and produces models of the system as core assets. These models are used through the whole system life-cycle, from implementation or validation to operation and maintenance. On the application side, the ontological framework has been used to develop a metacontrol engineering technology for autonomous systems, the OM Engineering Process (OMEP), to improve their runtime adaptivity and resilience. OMEP has been applied to a mobile robot in the form of a metacontroller built on top of the robot's control architecture. It exploits a functional model of the robot (TOMASys Model) to reconfigure its control if required by the situation at runtime. The functional model is based on a metamodel about controller function and structure using concepts form the ontology. The metacontroller was developed using the ontology-driven methodology and a robot control reference architecture.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Heideggerian AI and the Being of Robots},
author = {Carlos Herrera and Ricardo Sanz},
editor = {Vincent C Müller},
isbn = {978-3-319-26485-1},
year = {2016},
date = {2016-01-01},
booktitle = {Fundamental Issues of Artificial Intelligence},
pages = {497--513},
publisher = {Springer International Publishing},
address = {Cham},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
title = {Heideggerian AI and the being of robots},
author = {Carlos Herrera and Ricardo Sanz},
editor = {Vincent C Müller},
year = {2016},
date = {2016-01-01},
booktitle = {Fundamental Issues of Artificial Intelligence},
number = {377},
publisher = {Springer},
chapter = {29},
series = {Synthese Library},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
title = {Model-based Engineering of Autonomous Systems using Ontologies and Metamodels},
author = {Julia Bermejo-Alonso and Carlos Hernández and Ricardo Sanz},
year = {2016},
date = {2016-01-01},
booktitle = {IEEE International Symposium on Systems Engineering 2016 (IEEE ISSE 2016)},
address = {Edinburgh, Scotland},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Model Based Engineering of Process Plants using SysML},
author = {C Hernandez and M Rodriguez and I Diaz and R Sanz},
doi = {10.1016/B978-0-444-63428-3.50218-6},
issn = {15707946},
year = {2016},
date = {2016-01-01},
booktitle = {Computer Aided Chemical Engineering},
volume = {38},
abstract = {The motivation of this work is the constant evolution in the industry. Nowadays we are in what is called the fourth industrial revolution. This revolution is being fostered in many countries to get a more competitive industry. Industry 4.0 target is to make more efficient and flexible plants, reduce times and costs of projects and products lifecycle. Under this framework models appear as a core component in every new development. Using a systems engineering methodology the developed model will be the one that guarantees the consistency and derives the different applications needed in every stage of the lifecycle, from simulation, to risk assessment or even documentation maintenance. The objective of our work is to develop a model of a process plant using SysML. This model will follow a systems engineering approach, starting from the requirements and will cover the whole lifecycle of the Project. In this paper we present the development of the SysML model of a process plant (the production of ehtylbenzene from benzene and ethylene). The model includes the requirements as well as the structure, behaviour and activity diagrams. In this work an automatic transformation from the SysML model to a process simulation language (in this case Aspen Plus) has been built. This allows for the analysis of the process in the design and developement phases. The results of the simulation are fed back to the SysML model and this information is stored for further uses.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
title = {Requirements for building an ontology for autonomous robots},
author = {Behzad Bayat and Julita Bermejo-Alonso and Joel Carbonera and Tullio Facchinetti and Sandro Fiorini and Paulo Goncalves and Vitor A M Jorge and Maki Habib and Alaa Khamis and Kamilo Melo and Bao Nguyen and Joanna Isabelle Olszewska and Liam Paull and Edson Prestes and Veera Ragavan and Sajad Saeedi and Ricardo Sanz and Mae Seto and Bruce Spencer and Amirkhosro Vosughi and Howard Li},
isbn = {0143-991X},
year = {2016},
date = {2016-01-01},
journal = {Industrial Robot: An International Journal},
volume = {43},
number = {5},
pages = {469--480},
publisher = {Emerald},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2015
title = {Model-Based Metacontrol for Self-adaptation},
author = {Carlos Hernández and José L Fernández and Guadalupe Sánchez-Escribano and Julita Bermejo-Alonso and Ricardo Sanz},
editor = {Honghai Liu and Naoyuki Kubota and Xiangyang Zhu and Rüdiger Dillmann and Dalin Zhou},
year = {2015},
date = {2015-08-01},
booktitle = {Proceedings of the 8th International Conference on Intelligent Robotics and Applications, ICIRA 2015},
volume = {I},
pages = {643--654},
publisher = {Springer},
address = {Portsmouth},
series = {LNAI},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {The Exploitation of Models in Artificial Emotions},
author = {M G Sánchez-Escribano and C Herrera and R Sanz},
year = {2015},
date = {2015-01-01},
booktitle = {Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics},
pages = {154--169},
publisher = {IGI Global},
chapter = {6},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
title = {Model-based metacontrol for self-adaptation},
author = {C Hernández and J L Fernández and G Sánchez-Escribano and J Bermejo-Alonso and R Sanz},
doi = {10.1007/978-3-319-22879-2_58},
issn = {16113349},
year = {2015},
date = {2015-01-01},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {9244},
abstract = {There is an increasing demand for more autonomous systems. Enhancing systems with self-aware and self-adaptation capabilities can provide a solution to meet resilience needs. This article proposes a general design solution to build autonomous systems capable of runtime reconfiguration. The solution leverages Model-Driven Engineering with Model-Based Cognitive Control. The key idea is the integration of a metacontroller in the control architecture of the autonomous system, capable of perceiving the dysfunctional components of the control system and reconfiguring it, if necessary, at runtime. At the core of the metacontroller's operation lies a model of the system's functional architecture, which can be generated from the engineering modeling of the system.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
2014
title = {A Methodology for Predicting Abnormal Behaviors in Vessel Engines},
author = {Alberto Diez and José A Pagán and Ricardo Sanz},
year = {2014},
date = {2014-12-01},
booktitle = {2014 International Conference on Artificial Intelligence (ICOAI 2014)},
address = {Barcelona, Spain},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Improved Resilience Controllers Using Cognitive Patterns},
author = {Ricardo Sanz and Carlos Hernandez and Manuel Rodriguez and Julita Bermejo and Ignacio Lopez},
year = {2014},
date = {2014-08-01},
booktitle = {Proceedings of 19th IFAC World Congress},
pages = {683--688},
address = {Cape Town, South Africa},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Autonomous Acquisition of Natural Language},
author = {Eric Nivel and Kristinn R Thórisson and Bas R Steunebrink and Haris Dindo and Giovanni Pezzulo and Manuel Rodriguez and Carlos Hernandez and Dimitri Ognibene and Jürgen Schmidhuber and Ricardo Sanz and Helgi P Helgason and Antonio Chella and Gudberg K Jonsson},
year = {2014},
date = {2014-07-01},
booktitle = {Proceedings of IADIS International Conference on Intelligent Systems $backslash$& Agents 2014 (ISA-14)},
pages = {58--66},
address = {Lisbon, Portugal},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Plataforma para la implementación y validación de algoritmos de control de tiempo real en mini-helicópteros de varios rotores},
author = {Luis Ródenas and Ricardo Sanz and Pablo Albiol and Alberto Castillo and Daniel Verd{ú} and Pedro Garc$backslash$'$backslash$ia},
year = {2014},
date = {2014-01-01},
booktitle = {Jornadas de Automática},
address = {Valencia, Spain},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Bounded seed-AGI},
author = {Eric Nivel and Kristinn R Thórisson and Bas R Steunebrink and Haris Dindo and Giovanni Pezzulo and Manuel Rodríguez and Carlos Hernández and Dimitri Ognibene and Jürgen Schmidhuber and Ricardo Sanz and Helgi P Helgason and Antonio Chella},
doi = {10.1007/978-3-319-09274-4_9},
issn = {16113349},
year = {2014},
date = {2014-01-01},
booktitle = {International Conference on Artificial General Intelligence - AGI 2014},
volume = {8598 LNAI},
pages = {85--96},
abstract = {Four principal features of autonomous control systems are left both unaddressed and unaddressable by present-day engineering methodologies: (1) The ability to operate effectively in environments that are only partially known at design time; (2) A level of generality that allows a system to re-assess and re-define the fulfillment of its mission in light of unexpected constraints or other unforeseen changes in the environment; (3) The ability to operate effectively in environments of significant complexity; and (4) The ability to degrade gracefully - how it can continue striving to achieve its main goals when resources become scarce, or in light of other expected or unexpected constraining factors that impede its progress. We describe new methodological and engineering principles for addressing these shortcomings, that we have used to design a machine that becomes increasingly better at behaving in underspecified circumstances, in a goal-directed way, on the job, by modeling itself and its environment as experience accumulates. The work provides an architectural blueprint for constructing systems with high levels of operational autonomy in underspecified circumstances, starting from only a small amount of designer-specified code - a seed. Using value-driven dynamic priority scheduling to control the parallel execution of a vast number of lines of reasoning, the system accumulates increasingly useful models of its experience, resulting in recursive self-improvement that can be autonomously sustained after the machine leaves the lab, within the boundaries imposed by its designers. A prototype system named AERA has been implemented and demonstrated to learn a complex real-world task - real-time multimodal dialogue with humans - by on-line observation. Our work presents solutions to several challenges that must be solved for achieving artificial general intelligence. textcopyright 2014 Springer International Publishing.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {The embodiment of synthetic emotion},
author = {Carlos Herrera and María Guadalupe Sánchez-Escribano and Ricardo Sanz},
doi = {10.4018/978-1-4666-7278-9.ch009},
isbn = {9781466672796},
year = {2014},
date = {2014-01-01},
booktitle = {Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics},
pages = {204--212},
abstract = {Emotions are fundamentally embodied phenomena - but what exactly does this mean? And how is embodiment relevant for synthetic emotion? The specific role of embodied processes in the organisation of cognition and behaviour in biological systems is too complex to analyse without abstracting away the vast majority of variables. Robotic approaches have thus ignored physiological processes. At most, they hypothesise that homeostatic processes play a role in the cognitive economy of the agent - "gut feeling" is the embodied phenomenon to be modelled. Physiological processes play an actual role in the control of behaviour and interaction dynamics beyond information-processing. In this chapter, the authors introduce a novel approach to emotion synthesis based on the notion of morphofunctionality: the capacity to modulate the function of subsystems, changing the overall functionality of the system. Morphofunctionality provides robots with the capacity to control action readiness, and this in turn is a fundamental phenomenon for the emergence of emotion.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
Publications
Outline of a Brain Model for Self-Observing Agents Journal Article Journal of Artificial Intelligence and Consciousness, 8 (1), pp. 2150008, 2021, ISSN: 2705-0785. Functional self-awareness and metacontrol for underwater robot autonomy Journal Article Sensors (Switzerland), 21 (4), pp. 1–28, 2021, ISSN: 14248220. Ontological concepts for information sharing in cloud robotics Journal Article Journal of Ambient Intelligence and Humanized Computing, 2020, ISSN: 18685145. Understanding and Machine Consciousness Journal Article Journal of Artificial Intelligence and Consciousness, pp. 1–14, 2020, ISBN: 2705-0785. An Apology for the “Self” Concept in Autonomous Robot Ontologies Book 2020, ISSN: 21945365. Apologia for the ``Self'' Concept in Autonomous Robot Ontologies Inproceedings Proceedings of ROBOT'2019: Fourth Iberian Robotics Conference, Porto, Portugal, 2019. Deep evolutionary modeling of condition monitoring data in marine propulsion systems Journal Article Soft Computing, 23 (20), pp. 9937–9953, 2019, ISSN: 1433-7479. Deep evolutionary modeling of condition monitoring data in marine propulsion systems Journal Article Soft Computing, 23 (20), 2019, ISSN: 14337479. Specifying autonomy in the Internet of Things: the autonomy model and notation Book Springer Berlin Heidelberg, 2019, ISSN: 16179854. Consciousness, Engineering, and Anthropomorphism Journal Article APA Newsletter on Philosophy and Computers, 19 (1), pp. 12–18, 2019. Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming Journal Article Computers and Electronics in Agriculture, 161 , 2019, ISSN: 01681699. Consciousness and Understanding in Autonomous Systems Inproceedings Chella, Antonio; Gamez, David; Lincoln, Patrick; Manzotti, Riccardo; Pfautz, Jonathan (Ed.): Proceedings of the 2019 Towards Conscious AI Systems Symposium. AAAI Spring Symposium Series (AAAI SSS-19), Palo Alto, CA, 2019. Sharing Knowledge in the Intelligent Robot Life-cycle Miscellaneous WOSRA IROS 2018 Workshop on Collaboratively Working towards Ontology-based Standards for Robotics and Automation, 2018. Kernel-based support vector machines for automated health status assessment in monitoring sensor data Journal Article The International Journal of Advanced Manufacturing Technology, 95 (1-4), pp. 327–340, 2018, ISSN: 1433-3015. Metacognition for a Common Model of Cognition Inproceedings Procedia Computer Science, pp. 730–739, 2018, ISSN: 18770509. Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming Journal Article Computers and Electronics in Agriculture, 141-150 , 2018. Consciousness and understanding in autonomous systems Inproceedings CEUR Workshop Proceedings, 2018, ISSN: 16130073. A self-adaptation framework based on functional knowledge for augmented autonomy in robots Journal Article Integrated Computer-Aided Engineering, 25 (2), 2018, ISSN: 18758835. Towards an Ontology for Task and Planning in Autonomous Systems: An Emergency Scenario Incollection Ollero, Anibal; Sanfeliu, Alberto; Montano, Luis; Lau, Nuno; Cardeira, Carlos (Ed.): ROBOT 2017: Third Iberian Robotics Conference: Volume 1, pp. 429–440, Springer International Publishing, 2018, ISBN: 978-3-319-70833-1. A self-adaptation framework based on functional knowledge for augmented autonomy in robots Journal Article Integrated Computer-Aided Engineering, 25 , pp. 157–172, 2018. Kernel-based support vector machines for automated health status assessment in monitoring sensor data Journal Article International Journal of Advanced Manufacturing Technology, 95 (1-4), 2018, ISSN: 14333015. Towards an ontology for task and planning in autonomous systems: An emergency scenario Book 2018, ISSN: 21945357. Towards an Ontology for Task and Planning in Autonomous Systems: a Case Study for an Emergency Scenario Inproceedings ROBOT'2017 - Third Iberian Robotics Conference, Seville, Spain, 2017. Integral Management of Process Plants Systems through their Lifecycle using a Model-Based Engineering Approach Inproceedings ñ, Antonio Espu; Graells, Moises; Puigjaner, Luis (Ed.): Proceedings of the 27th European Symposium on Computer Aided Process Engineering -- ESCAPE 27, Barcelona, Spain, 2017. Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation Inproceedings 2017 International Conference on Cloud and Autonomic Computing (ICCAC), pp. 184–185, 2017. Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score Journal Article Neurocomputing, 241 , pp. 97–107, 2017, ISBN: 0925-2312. Ontology for autonomous robotics Inproceedings Proceedings of 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 189–194, IEEE, 2017, ISBN: 978-1-5386-3518-6. Kernel density-based pattern classification in blind fasteners installation Book 2017, ISSN: 16113349. Ontologies as Backbone of Cognitive Systems Engineering Inproceedings Proceedings of AISB CAOS 2017: Cognition And OntologieS, Bath, UK, 2017. Data-driven prognostics using a combination of constrained K-means clustering, fuzzy modeling and LOF-based score Journal Article Neurocomputing, 241 , 2017, ISSN: 18728286. Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation Inproceedings Proceedings - 2017 IEEE International Conference on Cloud and Autonomic Computing, ICCAC 2017, 2017, ISBN: 9781538619391. Kernel Density-Based Pattern Classification in Blind Fasteners Installation Incollection de Pisón, Francisco Javier Mart$backslash$'$backslash$inez; Urraca, Rubén; Quintián, Héctor; Corchado, Emilio (Ed.): Hybrid Artificial Intelligence Systems HAIS 2017, 10334 , pp. 195–206, Springer International Publishing, 2017. 2017, ISSN: 15707946. Ontology for autonomous robotics Inproceedings RO-MAN 2017 - 26th IEEE International Symposium on Robot and Human Interactive Communication, pp. 189–194, Lisbon, Portugal, 2017, ISBN: 9781538635186. Model-Based Engineering of Process Plants Using SysML Inproceedings Proceedings of the 26th European Symposium on Computer Aided Process Engineering, ESCAPE 26, pp. 1281–1286, Portorož, Slovenia, 2016. Model-based engineering of autonomous systems using ontologies and metamodels Inproceedings ISSE 2016 - 2016 International Symposium on Systems Engineering - Proceedings Papers, 2016, ISBN: 9781509007936. Heideggerian AI and the Being of Robots Book Chapter Müller, Vincent C (Ed.): Fundamental Issues of Artificial Intelligence, pp. 497–513, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-26485-1. Heideggerian AI and the being of robots Incollection Müller, Vincent C (Ed.): Fundamental Issues of Artificial Intelligence, (377), Springer, 2016. Model-based Engineering of Autonomous Systems using Ontologies and Metamodels Inproceedings IEEE International Symposium on Systems Engineering 2016 (IEEE ISSE 2016), Edinburgh, Scotland, 2016. Model Based Engineering of Process Plants using SysML Book 2016, ISSN: 15707946. Requirements for building an ontology for autonomous robots Journal Article Industrial Robot: An International Journal, 43 (5), pp. 469–480, 2016, ISBN: 0143-991X. Model-Based Metacontrol for Self-adaptation Inproceedings Liu, Honghai; Kubota, Naoyuki; Zhu, Xiangyang; Dillmann, Rüdiger; Zhou, Dalin (Ed.): Proceedings of the 8th International Conference on Intelligent Robotics and Applications, ICIRA 2015, pp. 643–654, Springer, Portsmouth, 2015. The Exploitation of Models in Artificial Emotions Incollection Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics, pp. 154–169, IGI Global, 2015. Model-based metacontrol for self-adaptation Book 2015, ISSN: 16113349. A Methodology for Predicting Abnormal Behaviors in Vessel Engines Inproceedings 2014 International Conference on Artificial Intelligence (ICOAI 2014), Barcelona, Spain, 2014. Improved Resilience Controllers Using Cognitive Patterns Inproceedings Proceedings of 19th IFAC World Congress, pp. 683–688, Cape Town, South Africa, 2014. Autonomous Acquisition of Natural Language Inproceedings Proceedings of IADIS International Conference on Intelligent Systems $backslash$& Agents 2014 (ISA-14), pp. 58–66, Lisbon, Portugal, 2014. Plataforma para la implementación y validación de algoritmos de control de tiempo real en mini-helicópteros de varios rotores Inproceedings Jornadas de Automática, Valencia, Spain, 2014. Bounded seed-AGI Inproceedings International Conference on Artificial General Intelligence - AGI 2014, pp. 85–96, 2014, ISSN: 16113349. The embodiment of synthetic emotion Incollection Handbook of Research on Synthesizing Human Emotion in Intelligent Systems and Robotics, pp. 204–212, 2014, ISBN: 9781466672796.
2021
2020
2019
2018
2017
2016
2015
2014