CV Lattes
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Universidade de São Paulo (USP). Escola Politécnica (EP) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Currently a postdoc researcher at the Advanced Institute for AI, Leno is a Doctor on Computer Engineering at the University of São Paulo (USP). He spent one year as a Research Scholar at the University of Texas at Austin in 2018-2019, where he was part of the Learning Agents Research Group (LARG), under supervision of Prof. Peter Stone. His previous titles are Bachelor of Science in Computer Science at Pontifical Catholic University of São Paulo (PUC-SP - 2012) and Master of Science in Electric Engineering, Computer Engineering area at University of São Paulo (USP - 2015). His main research interests are: Machine Learning, Reinforcement Learning, and Multiagent Systems. (Source: Lattes Curriculum)
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Reinforcement Learning is a powerful to train intelligent agents because the learning is performed completely autonomously. This learning is accomplished through repetitive interactions between agents and the environment through trial and error, until agents have enough information to properly actuate in order to solve a given task. However, an agent can take a long time to determine whic…
Reinforcement Learning (RL) is a popular solution to train autonomous agents to solve tasks in environments with unknown dynamics. Despite the recent successes of RL in solving increasingly challenging tasks, it suffers from an excessive requirement of samples of interactions with the environment in order to learn a good solution. When applied to Multiagent Systems (MAS), RL allows to tra…
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