6 citations · 9 across the 9 of their papers we have counts for
9 papers
Addressing Tactic Volatility in Self-Adaptive Systems Using Evolved Recurrent Neural Networks and Uncertainty Reduction Tactics
Aizaz Ul Haq, Niranjana Deshpande, AbdElRahman ElSaid +2
Self-adaptive systems frequently use tactics to perform adaptations. Tactic examples include the implementation of additional security measures when an intrusion is detected, or ac…
Continuous Ant-Based Neural Topology Search
AbdElRahman ElSaid, Joshua Karns, Zimeng Lyu +2
This work introduces a novel, nature-inspired neural architecture search (NAS) algorithm based on ant colony optimization, Continuous Ant-based Neural Topology Search (CANTS), whic…
An Experimental Study of Weight Initialization and Weight Inheritance Effects on Neuroevolution
Zimeng Lyu, AbdElRahman ElSaid, Joshua Karns +2
Weight initialization is critical in being able to successfully train artificial neural networks (ANNs), and even more so for recurrent neural networks (RNNs) which can easily suff…
Neuroevolutionary Transfer Learning of Deep Recurrent Neural Networks through Network-Aware Adaptation
AbdElRahman ElSaid, Joshua Karns, Alexander Ororbia +3
Transfer learning entails taking an artificial neural network (ANN) that is trained on a source dataset and adapting it to a new target dataset. While this has been shown to be qui…
Improving Neuroevolution Using Island Extinction and Repopulation
Zimeng Lyu, Joshua Karns, AbdElRahman ElSaid +1
Neuroevolution commonly uses speciation strategies to better explore the search space of neural network architectures. One such speciation strategy is through the use of islands, w…
The Ant Swarm Neuro-Evolution Procedure for Optimizing Recurrent Networks
AbdElRahman A. ElSaid, Alexander G. Ororbia, Travis J. Desell
Hand-crafting effective and efficient structures for recurrent neural networks (RNNs) is a difficult, expensive, and time-consuming process. To address this challenge, we propose a…