10 papers
Multi-Scale Structural Features for Continual, Comprehensible Visual Recognition in a Developmental Learning Framework
Zeki Doruk Erden
Contemporary machine learning struggles to learn continually, reuse prior knowledge, and expose a comprehensible internal structure. A recently proposed developmental, gradient-fre…
Evolution, Future of AI, and Singularity
Zeki Doruk Erden
This article critically examines the foundational principles of contemporary AI methods, exploring the limitations that hinder its potential. We draw parallels between the modern A…
Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence
Zeki Doruk Erden, Boi Faltings
Artificial intelligence (AI), propelled by advancements in machine learning, has made significant strides in solving complex tasks. However, the current neural network-based paradi…
On the Parallels Between Evolutionary Theory and the State of AI
Zeki Doruk Erden, Boi Faltings
This article critically examines the foundational principles of contemporary AI methods, exploring the limitations that hinder its potential. We draw parallels between the modern A…
Continual Reinforcement Learning via Autoencoder-Driven Task and New Environment Recognition
Zeki Doruk Erden, Donia Gasmi, Boi Faltings
Continual learning for reinforcement learning agents remains a significant challenge, particularly in preserving and leveraging existing information without an external signal to i…
A Proposal for Networks Capable of Continual Learning
Zeki Doruk Erden, Boi Faltings
We analyze the ability of computational units to retain past responses after parameter updates, a key property for system-wide continual learning. Neural networks trained with grad…