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…
Foundations of a Developmental Design Paradigm for Integrated Continual Learning, Deliberative Behavior, and Comprehensibility
Zeki Doruk Erden, Boi Faltings
Inherent limitations of contemporary machine learning systems in crucial areas -- importantly in continual learning, information reuse, comprehensibility, and integration with deli…
Agential AI for Integrated Continual Learning, Deliberative Behavior, and Comprehensible Models
Zeki Doruk Erden, Boi Faltings
Contemporary machine learning paradigm excels in statistical data analysis, solving problems that classical AI couldn't. However, it faces key limitations, such as a lack of integr…
Directed Structural Adaptation to Overcome Statistical Conflicts and Enable Continual Learning
Zeki Doruk Erden, Boi Faltings
Adaptive networks today rely on overparameterized fixed topologies that cannot break through the statistical conflicts they encounter in the data they are exposed to, and are prone…
Improved Cooperation by Exploiting a Common Signal
Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings
Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite…