Publications
Peer Reviewed Journal Publications
Queiroz, R. L.; Sampaio, F. F.; Lima, C.; Lima, P. M. V. 2021. AI from Concrete to Abstract (Demystifying Artificial Intelligence to the General Public). In AI & Society. v.36, 877-893. (In English). DOI: https://doi.org/10.1007/s00146-021-01151-x. Google Scholar Citations (16)
Abstract: Artificial intelligence (AI) has been adopted in a wide range of domains. This shows the imperative need to contribute to making citizens insightful actors in debates and decisions involving the adoption of AI mechanisms. Currently, existing approaches to the teaching of basic AI concepts through programming treat machine intelligence as an external element/module. After being trained, that external module is coupled to the main application. Combining block-based programming and WiSARD weightless artificial neural networks, this article presents the conceptualization and design of a new methodology, AI from concrete to abstract (AIcon2abs), to endow general people (including children) with a minimum understanding of what AI means. The main strategy adopted was to include AI training and classification primitives as blocks that compose an otherwise conventional computer program. This way, the programmer can use these blocks as he/she uses other programming constructs. In order to achieve this purpose, we also propose BlockWiSARD, a block-based programming environment designed to promote the demystification of artificial intelligence via practical activities related to the development of learning machines, as well as through the observation of their learning process. As a beneficial side effect of BlockWiSARD, the difference between a program capable of learning from data and a conventional computer program becomes more evident. In addition, the simplicity of the WiSARD weightless artificial neural network model enables easy visualization and understanding of training and classification tasks internal realization.
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Peer Reviewed Conference Proceedings Publications
Queiroz, R. L.; Coutinho, I. B. A.; Xexeo, G. B.; Lima, P. M. V.; Sampaio, F. F. 2018. Playing with Robots Using Your Brain In 2018 17th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames). IEE. (In English) DOI: https://doi.org/10.1109/SBGAMES.2018.00031. Google Scholar Citations (14)
Abstract: The use of EEG (electroencephalography) has been perceived as an interesting tool for people with motor disabilities to control a sort of electronic devices like robotic wheelchairs, exoskeletons, robotic arms, computers, among others. This kind of BCI (Brain Computer Interface) can be useful to help those people to carry out daily chores as well as to engage in recreational activities, like playing games, just for fun or as a way of performing the necessary training for the mental control of electronic devices in a playful way. In this sense, this paper presents a proposal for a Hot and Cold game using a Turtlebot3 Waffle robot and an EMOTIV Insight 5 channel mobile EEG.
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Book Chapters
Sampaio, F. F.; Miranda, L.C.; Elia, M.; Brandão, S.; Bomfim, M.N.; Pinto, M.C.; Bastos, C.A.R; Queiroz, R. L.; Souza, P.R.A; Bento, M.A.; Rocha, R.N. 2019. Consórcio de Laboratórios Remotos para Robótica Educacional - labVAD. In Robótica Educacional - experiências inovadoras na educação brasileira, edited by Rodrigo Barbosa e Silva; Paulo Blikstein. e ed 1. Vol. 1, 169-190. Porto Alegre: Penso Editora. (In Portuguese) ISBN-10: 858429189X
Abstract: In Chapter 12, Consortium of remote laboratories for the practice of educational robotics - LabVAD, Fábio Ferrentini Sampaio, Leonardo Cunha de Miranda, Marcos Elia, Serafim Brandão, Maurício Nunes da Costa Bomfim, Marcos de Castro Pinto, César A. R. Bastos, Rubens Lacerda Queiroz, Paulo Roberto de Azevedo Souza, Murilo de Araújo Bento and Raphael Netto Castello Branco Rocha introduce us to the Informatics Applied to Education Group (Ginape) of the Tércio Pacitti Institute of Computational Applications and Research (NCE) of the Federal University of Rio de Janeiro (UFRJ ) in a historical journey of 30 years that culminated in the creation of the Virtual Didactic Laboratory (LabVAD). The chapter addresses the guiding principles of the didactic-pedagogical-technological choices made by the team, a detailed description of the current version of the LabVAD environment, and the main actions and subprojects carried out and in progress. The authors consider that the project's next steps are expanding the diversity of teaching science and robotics laboratories and seeking partnerships with teaching and research institutions in other regions of the country and abroad. The LabVAD platform is fully operational and available for access via the Internet from anywhere and on any day and time.
Preprints
Queiroz, R.L.; Lima, C.; Sampaio, F.F.; Lima, P.M.V. 2024. How do machines learn? Evaluating the AIcon2abs method. arXiv:2401.07386v1 [cs.CY]. DOI: https://doi.org/10.48550/arXiv.2401.07386
Abstract: This paper evaluates AIcon2abs (Queiroz et al., 2021), a recently proposed method that enables awareness among the general public on machine learning. Such is possible due to the use of WiSARD, an easily understandable machine learning mechanism, thus requiring little effort and no technical background from the target users. WiSARD is adherent to digital computing; training consists of writing to RAM-type memories, and classification consists of reading from these memories. The model enables easy visualization and understanding of training and classification tasks' internal realization through ludic activities. Furthermore, the WiSARD model does not require an Internet connection for training and classification, and it can learn from a few or one example. This feature makes it easier to observe the machine, increasing its accuracy on a particular task with each new example used. WiSARD can also create "mental images" of what it has learned so far, evidencing key features pertaining to a given class. The assessment of the AIcon2abs method's effectiveness was conducted through the evaluation of a remote course with a workload of approximately 6 hours. It was completed by thirty-four Brazilian subjects: 5 children between 8 and 11 years old; 5 adolescents between 12 and 17 years old; and 24 adults between 21 and 72 years old. Data analysis adopted a hybrid approach. AIcon2abs was well-rated by almost 100% of the research subjects, and the data collected revealed quite satisfactory results concerning the intended outcomes. This research has been approved by the CEP/HUCFF/FM/UFRJ Human Research Ethics Committee.
REFERENCES
Queiroz, R. L.; Sampaio, F. F.; Lima, C.; Lima, P. M. V. 2021. AI from Concrete to Abstract (Demystifying Artificial Intelligence to the General Public). In AI & Society. v.36, 877-893. (In English). DOI: https://doi.org/10.1007/s00146-021-01151-x.