Andrea Galassi Home Page

 

Andrea Galassi

1st year PhD student

DISI, Università di Bologna
Viale del Risorgimento 2, 40136 - Bologna (IT)

email: a<dot>galassi<at>unibo<dot>it

Profiles:

 

I am a first year PhD student at the DISI department of the University of Bologna, working on Machine Learning techniques applied to Argumentation Mining, but also to Games and Constraint Satisfaction Problems. My supervisor is Professor Paolo Torroni.

For my Master Thesis, I've applied Deep Neural Networks to a board game, Nine Men's Morris, generating a dataset useful for future Machine Learning work and investigating the ability of the DNNs to learn the rules of a game from scratch. More information about this study are available here.

We have expanded it to the subject of Constraint Satisfaction Problems, to understand whether DNNs can solve problems just by watching some solutions.

For my PhD, I'm studying Argumentation Mining and related topics, working on how to merge symbolic and subsymbolic techniques.

I've been teaching assistant ("Tutor Didattico") of professors Paola Mello, Federico Chesani, and Paolo Torroni. I am also co-supervisor in some bachelor thesis, maters thesis, and course projects, most of them regarding machine learning application.

I have visited the Stanford University during the summer 2018, working under the supervision of Margaret Hagan in the contex of the MIREL project.

 

Recent works and news:

 

Projects in which I am or I've been involved:

 

Publications

  

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2018
Galassi, A., M. Lippi, and P. Torroni, "Argumentative Link Prediction using Residual Networks and Multi-Objective Learning", Proceedings of the 5th Workshop on Argument Mining, Brussels, Belgium, Association for Computational Linguistics, pp. 1–10, 11/2018. Abstract
application/pdf iconArgMining18-PRE.pdf
Galassi, A., M. Lombardi, P. Mello, and M. Milano, "Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study", Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Cham, Springer International Publishing, pp. 254–262, 06/2018. Abstract
application/pdf iconCSP-DL-POST_PRINT.pdf
Chesani, F., A. Galassi, M. Lippi, and P. Mello, "Can Deep Networks Learn to Play by the Rules? A Case Study on Nine Men's Morris", IEEE Transactions on Games, vol. PP, issue 99, no. 99, pp. 1-10, 02/2018. Abstract
application/pdf iconCanDNNplayNMM-Accepted.pdf
Galassi, A., M. Lombardi, P. Mello, and M. Milano, "Deep Neural Networks for Constraint Satisfaction Problems: an Initial Investigation for the N-Queens", OLA 2018: International Workshop on Optimization and Learning: Challenges and Application, Alicante, Spain, 02/2018.
application/pdf iconOLA FINALE.pdf
2017
Galassi, A., Symbolic versus sub-symbolic approaches: a case study on training Deep Networks to play Nine Men's Morris game, , Bologna, University of Bologna (Italy), Mar, 2017. Abstract
Chesani, F., A. Galassi, P. Mello, and G. Trisolini, "A Game-Based Competition as Instrument for Teaching Artificial Intelligence", AI*IA 2017 Advances in Artificial Intelligence: XVIth International Conference of the Italian Association for Artificial Intelligence, Bari, Italy, November 14-17, 2017, Proceedings, vol. 10640, Bari, Italy, Springer International Publishing, pp. 72–84, 11/2017. Abstract
application/pdf iconMULINO COMPETITION PRE PRINT.pdf
application/pdf iconPOSTER COMPETITION.pdf