4 papers · 1 filter
Ergodic Risk Measures: Towards a Risk-Aware Foundation for Continual Reinforcement Learning
Juan Sebastian Rojas, Chi-Guhn Lee
Continual reinforcement learning (continual RL) seeks to formalize the notions of lifelong learning and endless adaptation in RL. In particular, the aim of continual RL is to devel…
A Contrastive Diffusion-based Network (CDNet) for Time Series Classification
Yaoyu Zhang, Chi-Guhn Lee
Deep learning models are widely used for time series classification (TSC) due to their scalability and efficiency. However, their performance degrades under challenging data condit…
A Differential Perspective on Distributional Reinforcement Learning
Juan Sebastian Rojas, Chi-Guhn Lee
To date, distributional reinforcement learning (distributional RL) methods have exclusively focused on the discounted setting, where an agent aims to optimize a discounted sum of r…
Burning RED: Unlocking Subtask-Driven Reinforcement Learning and Risk-Awareness in Average-Reward Markov Decision Processes
Juan Sebastian Rojas, Chi-Guhn Lee
Average-reward Markov decision processes (MDPs) provide a foundational framework for sequential decision-making under uncertainty. However, average-reward MDPs have remained largel…