12 citations · 67 across the 68 of their papers we have counts for
72 papers
Exploration-Preserving Policy Optimization
Hangzhan jin, Mohammad Hamdaqa, Doina Precup
Reinforcement learning with verifiable rewards improves reasoning, while the allocation of learning signal shapes which solutions remain accessible under repeated sampling. Group-r…
From Connectivity to Rewards: Dense Reward Learning with Directed State Graphs
Shuyuan Zhang, Zihan Wang, Xiao-Wen Chang +1
The integration of graphs with Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) has received increasing attention, as graphs naturally encode task hierarchies for effec…
A Bellman Optimality Equation for Plasticity
Jeremy Lucas, Doina Precup
In continual reinforcement learning, carefully managing the stability-plasticity tradeoff remains a core challenge. Recent work by Abel et al. (2025) formalized this dilemma by def…
SIC-Agents: Benchmarking and Building an Adaptive Simulator for Pediatric Serious Illness Communication Training
Zihan Wang, Anita Marie Slominska, Rennie Bimman +10
Pediatric serious illness communication (SIC) is critically important, yet scalable communication training for clinicians remains limited. Compared with other dialogue simulation s…
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…