45 citations · 59 across the 14 of their papers we have counts for
7 papers · 1 filter
In Two Minds about Lifelong Learning: Exploring Hemispheric Redundancy and Specialisation in Neural Models
Benjamin Smith, Levin Kuhlmann, Kaushik Roy +1
Persistent intelligent systems require the ability to learn continually, but current machine learning approaches face significant challenges in this area compared to biological lea…
ARROW: Augmented Replay for RObust World models
Abdulaziz Alyahya, Abdallah Al Siyabi, Markus R. Ernst +3
Continual reinforcement learning challenges agents to acquire new skills while retaining previously learned ones with the goal of improving performance in both past and future task…
Active perception and disentangled representations allow continual, episodic zero and few-shot learning
David Rawlinson, Gideon Kowadlo
Generalization is often regarded as an essential property of machine learning systems. However, perhaps not every component of a system needs to generalize. Training models for gen…
Graceful task adaptation with a bi-hemispheric RL agent
Grant Nicholas, Levin Kuhlmann, Gideon Kowadlo
In humans, responsibility for performing a task gradually shifts from the right hemisphere to the left. The Novelty-Routine Hypothesis (NRH) states that the right and left hemisphe…
Augmenting Replay in World Models for Continual Reinforcement Learning
Luke Yang, Levin Kuhlmann, Gideon Kowadlo
Continual RL requires an agent to learn new tasks without forgetting previous ones, while improving on both past and future tasks. The most common approaches use model-free algorit…
One-shot learning for the long term: consolidation with an artificial hippocampal algorithm
Gideon Kowadlo, Abdelrahman Ahmed, David Rawlinson
Standard few-shot experiments involve learning to efficiently match previously unseen samples by class. We claim that few-shot learning should be long term, assimilating knowledge…
Unsupervised One-shot Learning of Both Specific Instances and Generalised Classes with a Hippocampal Architecture
Gideon Kowadlo, Abdelrahman Ahmed, David Rawlinson
Established experimental procedures for one-shot machine learning do not test the ability to learn or remember specific instances of classes, a key feature of animal intelligence.…