3 papers
cs.LG2026
Distributions as Actions: A Unified Framework for Diverse Action Spaces
Jiamin He, A. Rupam Mahmood, Martha White
We introduce a novel reinforcement learning (RL) framework that treats parameterized action distributions as actions, redefining the boundary between agent and environment. This re…
cs.LG2026
Revisiting Mixture Policies in Entropy-Regularized Actor-Critic
Jiamin He, Samuel Neumann, Jincheng Mei +2
Mixture policies theoretically offer greater flexibility than unimodal policies in continuous action reinforcement learning, but the practical benefits of this complexity remain el…
cs.LG2025
Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
Gautham Vasan, Mohamed Elsayed, Alireza Azimi +5
Modern deep policy gradient methods achieve effective performance on simulated robotic tasks, but they all require large replay buffers or expensive batch updates, or both, making…