no code implementations • 26 May 2022 • Rafael B. Audibert, Henrique Lemos, Pedro Avelar, Anderson R. Tavares, Luís C. Lamb
This work also contributes, to a certain extent, to shed new light on the history and evolution of AI by exploring the dynamics involved in the field's evolution by looking at papers published at the flagship AI and machine learning conferences since the first International Joint Conference on Artificial Intelligence (IJCAI) held in 1969.
2 code implementations • 13 Sep 2020 • Marcio Nicolau, Anderson R. Tavares, Zhiwei Zhang, Pedro Avelar, João M. Flach, Luis C. Lamb, Moshe Y. Vardi
Computational learning theory states that many classes of boolean formulas are learnable in polynomial time.
no code implementations • 5 May 2020 • Henrique Lemos, Pedro Avelar, Marcelo Prates, Luís Lamb, Artur Garcez
The recent developments and growing interest in neural-symbolic models has shown that hybrid approaches can offer richer models for Artificial Intelligence.
no code implementations • 29 Feb 2020 • Luis C. Lamb, Artur Garcez, Marco Gori, Marcelo Prates, Pedro Avelar, Moshe Vardi
Neural-symbolic computing has now become the subject of interest of both academic and industry research laboratories.
2 code implementations • 11 Mar 2019 • Henrique Lemos, Marcelo Prates, Pedro Avelar, Luis Lamb
Our results thus contribute to the standing challenge of integrating robust learning and symbolic reasoning in Deep Learning systems.