activity
20242026
collaborators

34 papers

cs.LG2026

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…

cs.LG2026

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…

stat.ML2026

To Retain or to Adapt? Generalizing Continual Learning

Giulia Lanzillotta, Mandana Samiei, Doina Precup +2

The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on a pervasive, often unstated assumption: that…

cs.CL2026

Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?

Mandana Samiei, Eunice Yiu, Anthony GX-Chen +5

A long-standing finding in the causal learning literature is that adults struggle to identify conjunctive causal rules, where an effect requires the simultaneous presence of multip…

cs.LG2026

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…

cs.LG2026

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…