3 papers
cs.LG2023
GloNets: Globally Connected Neural Networks
Antonio Di Cecco, Carlo Metta, Marco Fantozzi +2
Deep learning architectures suffer from depth-related performance degradation, limiting the effective depth of neural networks. Approaches like ResNet are able to mitigate this, bu…
cs.AI2019
SAI: a Sensible Artificial Intelligence that plays with handicap and targets high scores in 9x9 Go (extended version)
Francesco Morandin, Gianluca Amato, Marco Fantozzi +3
We develop a new model that can be applied to any perfect information two-player zero-sum game to target a high score, and thus a perfect play. We integrate this model into the Mon…
cs.AI2018
SAI, a Sensible Artificial Intelligence that plays Go
Francesco Morandin, Gianluca Amato, Rosa Gini +3
We propose a multiple-komi modification of the AlphaGo Zero/Leela Zero paradigm. The winrate as a function of the komi is modeled with a two-parameters sigmoid function, so that th…