A TD3 variant that evaluates multiple perturbed actions via short Monte Carlo rollouts reports faster learning and higher returns on HalfCheetah, Walker2d, and Swimmer.
”A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management.” Information Fusion (2024): 102369
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control
A TD3 variant that evaluates multiple perturbed actions via short Monte Carlo rollouts reports faster learning and higher returns on HalfCheetah, Walker2d, and Swimmer.