3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.AI2022★ 3 cited
Reinforcement Learning with Brain-Inspired Modulation can Improve Adaptation to Environmental Changes
Eric Chalmers, Artur Luczak
Developments in reinforcement learning (RL) have allowed algorithms to achieve impressive performance in highly complex, but largely static problems. In contrast, biological learni…
cs.NE2022★ 1 cited
Biologically-inspired neuronal adaptation improves learning in neural networks
Yoshimasa Kubo, Eric Chalmers, Artur Luczak
Since humans still outperform artificial neural networks on many tasks, drawing inspiration from the brain may help to improve current machine learning algorithms. Contrastive Hebb…