Difference between revisions of "User:EwertonLopes"

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(PhD Research)
 
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== PhD Research ==
 
== PhD Research ==
My [[Robogame_Strategy| PhD research project]] proposes to investigate how to develop complex strategy-based abilities in autonomous robots for the purpose of designing better Physically Interactive Robogames (PIRG) by the use of machine learning (ML) techniques. Specifically, I tackle the development of player modelling (which includes a minimalist approach to intention detection) for strategy adjustment with the aim of keeping (or raising) the human player engagement.
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My [[Robogame_Strategy| PhD research project]] proposes to investigate how to develop complex strategy-based abilities in autonomous robots for the purpose of designing better Physically Interactive Robogames (PIRG) by the use of machine learning (ML) techniques. Specifically, I tackle the development of player modelling (which should also include an approach to intention detection) for strategy adjustment with the aim of keeping (or raising) the human player engagement.

Latest revision as of 14:10, 26 August 2015

Ewerton Lopes
Foto di EwertonLopes


E-Mail: ewerton.lopes@polimi.it
Advisor:
Research Areas:


Project page(s):
Status: active

Hi. I'm a PhD student from Politecnico di Milano (POLIMI). I have a Master of Science degree in informatics from Universidade Federal da Paraíba, in Brazil (2015). I got my major degree (licentiate) in Computer Science from the same university in 2013. Currently at POLIMI, I have the support from the Brazilian National Council for Scientific and Technological Development (CNPq).

Research Interests

My main research interests are:

  • Artificial Intelligence and bio-inspired computational models;
  • Probabilistic reasoning and Machine Learning (specially classification models);
  • Intelligent autonomous agents;
  • Robogames


PhD Research

My PhD research project proposes to investigate how to develop complex strategy-based abilities in autonomous robots for the purpose of designing better Physically Interactive Robogames (PIRG) by the use of machine learning (ML) techniques. Specifically, I tackle the development of player modelling (which should also include an approach to intention detection) for strategy adjustment with the aim of keeping (or raising) the human player engagement.