36 papers · 1 filter
Analytic Planning under Uncertainty with Moment Closure
Shishir Sharma, Doina Precup
Effective model-based reinforcement learning in stochastic environments requires planning that accounts for predictive uncertainty. Propagating full state distributions analyticall…
Adaptive Multi-Horizon Reinforcement Learning
Manoosh Samiei, Doina Precup, Paul Masset
Effective decision-making in complex and changing environments requires balancing short-term and long-term consequences. In reinforcement learning (RL), this trade-off is typically…
Using Reward Uncertainty to Induce Diverse Behaviour in Reinforcement Learning
Anthony GX-Chen, Ankit Anand, Gheorghe Comanici +7
Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applications such as language model fin…
Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems
Jonathan Colaço Carr, Jonathan Colaço Carr, Prakash Panangaden +2
Reinforcement learning with scalar rewards is widely used for aligning machine-learning systems with user preferences. But, pairwise preferences are often more natural for users to…
Balancing Plasticity and Stability with Fast and Slow Successor Features
Raymond Chua, Doina Precup, Blake Richards
A hallmark of intelligence is the ability to adapt in non-stationary environments, yet deep Reinforcement Learning (RL) agents often struggle in such settings. Prior studies introd…
Rotation-Preserving Supervised Fine-Tuning
Hangzhan Jin, Tianwei Ni, Lu Li +3
Supervised fine-tuning (SFT) improves in-domain performance but can degrade out-of-domain (OOD) generalization. Prior work suggests that this degradation is related to changes in d…