17 citations · 54 across the 14 of their papers we have counts for
6 papers · 1 filter
Deep Reinforcement Learning with Modulated Hebbian plus Q Network Architecture
Pawel Ladosz, Eseoghene Ben-Iwhiwhu, Jeffery Dick +6
This paper presents a new neural architecture that combines a modulated Hebbian network (MOHN) with DQN, which we call modulated Hebbian plus Q network architecture (MOHQA). The hy…
Generative Continual Concept Learning
Mohammad Rostami, Soheil Kolouri, James McClelland +1
After learning a concept, humans are also able to continually generalize their learned concepts to new domains by observing only a few labeled instances without any interference wi…
Attention-Based Structural-Plasticity
Soheil Kolouri, Nicholas Ketz, Xinyun Zou +2
Catastrophic forgetting/interference is a critical problem for lifelong learning machines, which impedes the agents from maintaining their previously learned knowledge while learni…
Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
Mohammad Rostami, Soheil Kolouri, Praveen K. Pilly
Despite huge success, deep networks are unable to learn effectively in sequential multitask learning settings as they forget the past learned tasks after learning new tasks. Inspir…
Continual Learning Using World Models for Pseudo-Rehearsal
Nicholas Ketz, Soheil Kolouri, Praveen Pilly
The utility of learning a dynamics/world model of the environment in reinforcement learning has been shown in a many ways. When using neural networks, however, these models suffer…
Neuromodulated Goal-Driven Perception in Uncertain Domains
Xinyun Zou, Soheil Kolouri, Praveen K. Pilly +1
In uncertain domains, the goals are often unknown and need to be predicted by the organism or system. In this paper, contrastive excitation backprop (c-EB) was used in a goal-drive…