4 papers
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…
Communication in modular robotic motor control: Bilateral controllers under realistic constraints
Jingwen Li, Levin Kuhlmann, Jason Friedman +1
Robotic motor control in musculoskeletal systems requires fast, accurate movement and robust postural stabilization under signal-dependent noise (where motor command variance scale…
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…