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Dr. Valeria Javalera holds a PhD (cum laude) in Automatic Robotics and Vision from the Polytechnic University of Catalonia (UPC), Barcelona, Spain as well as an MSc in Computer Science and Engineering in Computer Systems (specialization in Software Engineering) from the Technological Institute of Hermosillo.
As a PhD fellow at CONACYT, she worked at the Institute of Robotics and Industrial Informatics (IRI) of the CSIC (Spain's Higher Council of Scientific Research) where she collaborated on projects related to the distributed control of Large Scale Systems (LSS), specifically with integrated water cycle management projects such as the WIDE project funded by the European Union and the WATMAN and ITACA projects funded by the Spanish government.
Dr. Javalera has participated in international congresses and published work related to the development of new distributed control techniques for LSS with predictive control based on models, machine learning applied to automation, systems identification and control with multi-agent systems, optimization and system modeling etc.
Since 2002, she has been a professor at the Instituto Tecnologico Superior de Cajeme (ITESCA) teaching at the Computer Systems Engineering (ISC) department as well as in the Master in Mechatronics Engineering (MIMEC). She is a member of the postgraduate council of the MIMEC. She is founding member of the Ibero-American Network in Artificial Intelligence (RIIA) and consultant in the area of technological development at SEKAI S.A. de C.V.
Dr. Javalera has designed an architecture and a methodology to deal with the interaction between systems (or sub-systems) in a distributed control architecture for LSS. This approach combines ideas from Distributed Artificial Intelligence (DAI) and Reinforcement Learning (RL) in order to provide a controller interaction based on negotiation, cooperation and learning techniques. The aim of this methodology is to provide a general structure to perform optimal control in networked distributed environments, where multiple dependencies between subsystems are found.
Dr. Valeria Javalera is currently an IIASA-CONACYT postdoc fellow at the International Institute for Applied Systems Analysis. She participates in the Advanced Systems Analysis (ASA) program and the Ecosystems Services and Management (ESM) program as well. She researches the optimal distribution of resources in large-scale systems, distributed optimization, machine learning, and Distributed computing. She is currently working on the FABLE Project (Food, Agriculture, Biodiversity, Land, and Energy), where she is responsible for the development and administration of the Linker platform.
Last update: 06-FEB-2019
Rovenskaya E, Aghababaei Samani K, Baklanov A , Ermolieva T, Folberth C , Fritz S, Hadi H, Javalera Rincón V , et al. (2019). Artificial Intelligence and Machine Learning for Systems Analysis of the 21st Century. IIASA Working Paper. Laxenburg, Austria: WP-19-010
FABLE 2019 (2019). Pathways to Sustainable Land-Use and Food Systems. International Institute for Applied Systems Analysis (IIASA) and the Sustainable Development Solutions Network (SDSN)
Javalera Rincón V , Cayuela VP, Seix BM, & Orduña-Cabrera F (2019). Cooperative Linker for the Distributed Control of the Barcelona Drinking Water Network. In: Proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART 2019). pp. 560-567 Porto, Portugal: ICAART. ISBN 978-989-758-350-610.5220/0007349105600567.
Javalera Rincón V , Cayuela VP, Seix BM, & Orduña-Cabrera F (2019). Reinforcement Learning Approach for Cooperative Control of Multi-Agent Systems. In: Proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART 2019). pp. 80-91 Porto, Portugal: ICAART. ISBN 978-989-758-350-610.5220/0007349000800091.
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