9 citations · 9 across the 3 of their papers we have counts for
3 papers
Mitigating Value Hallucination in Dyna Planning via Multistep Predecessor Models
Farzane Aminmansour, Taher Jafferjee, Ehsan Imani +3
Dyna-style reinforcement learning (RL) agents improve sample efficiency over model-free RL agents by updating the value function with simulated experience generated by an environme…
AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games
Neil Burch, Martin Schmid, Matej Moravčík +1
Evaluating agent performance when outcomes are stochastic and agents use randomized strategies can be challenging when there is limited data available. The variance of sampled outc…
Alignment Based Kernel Learning with a Continuous Set of Base Kernels
Arash Afkanpour, Csaba Szepesvari, Michael Bowling
The success of kernel-based learning methods depend on the choice of kernel. Recently, kernel learning methods have been proposed that use data to select the most appropriate kerne…