1 citations · 2 across the 6 of their papers we have counts for
7 papers
Beating Transformers using Synthetic Cognition
Alfredo Ibias, Miguel Rodriguez-Galindo, Hector Antona +2
The road to Artificial General Intelligence goes through the generation of context-aware reactive behaviors, where the Transformer architecture has been proven to be the state-of-t…
The Function-Representation Model of Computation
Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda +2
Cognitive Architectures are the forefront of the research into developing an artificial cognition. However, they approach the problem from a separated memory and program model of c…
Reducing Diversity to Generate Hierarchical Archetypes
Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda +2
The Artificial Intelligence field seldom address the development of a fundamental building piece: a framework, methodology or algorithm to automatically build hierarchies of abstra…
Knowledge Discovery using Unsupervised Cognition
Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda +1
Knowledge discovery is key to understand and interpret a dataset, as well as to find the underlying relationships between its components. Unsupervised Cognition is a novel unsuperv…
Unsupervised Cognition
Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda +2
Unsupervised learning methods have a soft inspiration in cognition models. To this day, the most successful unsupervised learning methods revolve around clustering samples in a mat…
Improving Noise Robustness through Abstractions and its Impact on Machine Learning
Alfredo Ibias, Karol Capala, Varun Ravi Varma +2
Noise is a fundamental problem in learning theory with huge effects in the application of Machine Learning (ML) methods, due to real world data tendency to be noisy. Additionally,…
From Manifestations to Cognitive Architectures: a Scalable Framework
Alfredo Ibias, Guillem Ramirez-Miranda, Enric Guinovart +1
The Artificial Intelligence field is flooded with optimisation methods. In this paper, we change the focus to developing modelling methods with the aim of getting us closer to Arti…