10 citations · 12 across the 5 of their papers we have counts for
5 papers
SingularClip: Preventing Spectral Collapse to Maintain Plasticity in Continual and Reinforcement Learning
Tyler Kastner, Nimrod De La Vega, Amir-massoud Farahmand
Neural networks trained on nonstationary tasks frequently lose the ability to fit new targets, a phenomenon referred to as loss of plasticity. We identify a novel source of plastic…
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning
Claas Voelcker, Tyler Kastner, Igor Gilitschenski +1
We investigate the impact of auxiliary learning tasks such as observation reconstruction and latent self-prediction on the representation learning problem in reinforcement learning…
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes
Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden +1
Behavioural metrics have been shown to be an effective mechanism for constructing representations in reinforcement learning. We present a novel perspective on behavioural metrics f…
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
Tyler Kastner, Murat A. Erdogdu, Amir-massoud Farahmand
We consider the problem of learning models for risk-sensitive reinforcement learning. We theoretically demonstrate that proper value equivalence, a method of learning models which…
MICo: Improved representations via sampling-based state similarity for Markov decision processes
Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden +1
We present a new behavioural distance over the state space of a Markov decision process, and demonstrate the use of this distance as an effective means of shaping the learnt repres…