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Universidade Federal do Rio Grande do Sul (UFRGS). Instituto de Informática (Institutional affiliation from the last research proposal) Birthplace: Brazil
Ana Bazzan received her PhD in 1997 from the University of Karlsruhe, Germany. Her previous degrees are in Engineering from the Politechnic School of the University of São Paulo, Brazil, and an MSc. in Computer Science from the Institute of Informatics at the University of Rio Grande do Sul (UFRGS) in Porto Alegre, Brazil.From 1997 to 1998, she had a postdoc research associate position in the Multi-Agent Systems Laboratory at the University of Massachusetts in Amherst, under the supervision of Prof. Victor Lesser. In 1999 she joined the Institute for Informatics at UFRGS where she now is an Associate Professor.She is affiliated with the research group on Artificial Intelligence and Multi-Agent Systems at UFRGS, where she is a full professor. Her research interests include: Game-Theoretic Paradigms for Coordination of Agents, Multiagent Learning, Coordination and Cooperation in MAS, Agent-Based Simulation, Iterated Prisoner's Dilemma and other games, and Traffic Simulation and Control.Other professional activities: keynote speaker at the 2017 AAMAS conference, member of the IFAAMAS (Int. Foundation for Multiagent Systems) board (2004-2008 and 2014-2020), associate editor of the J. of Vehicle Routing Algorithms (2017-), Journal of Autonomous Agents and Multiagent Systems (2010-2017), member of the editorial board of the journals Advances in Complex Systems (2007-2017), Multiagent and Grid Systems (until 2017), president of the steering committee of the special interest group on Artificial Intelligence of the Brazilian Computing Society (2004-2006), member of the steering committee of the the special interest group on Bioinformatics of the Brazilian Computing Society, co-general chair of the AAMAS 2014 (the premier conference on autonomous agents and multiagent systems), area chair of the IJCAI 2017, general chair of MATES 2014, PC chair of the 2017 PRIMA conference, 17th Braz. Symp. on Artificial Intelligence (2004) and co-organizer of Workshop on Agents in Traffic and Transportation. (Source: Lattes Curriculum)
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Machine learning is being used in the area of urban mobility. In particular, reinforcement learning (RL) is a technique that is frequently used since it allows agents to adapt to the state of the traffic. However, the literature on RL rarely discusses works that tackle multiobjective decision making, that are key in this domain. This way, the goal of this project is to develop a framework…
Estimates show that the loss of time in traffic in Brazil generates losses of billions of Brazilian reais per year.Although Brazilian traffic authorities act au pair with the most effective techniques in traffic engineering, the use of Internet has evolved little in this area.As a consequence, one has an interesting panorama in Brazil: users (of public as well as private transportation me…
(Only some records are available in English at this moment)
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