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Sep 1, 2023 · This paper further develops a new policy ensemble gradient (PEG) algorithm for DRL, inspired by the recent success of several ensemble DRL algorithms.
Nov 9, 2022 · Policy gradient algorithms for reinforcement learning (RL) have successfully tackled a broad range of high-dimensional continuous RL problems, ...
Policy ensemble gradient for continuous control problems in deep reinforcement learning ... learning with multiple deep deterministic policy gradient ...
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Nov 30, 2021 · We show how existing tools can be brought together in a novel way, giving rise to the Ensemble Deep Deterministic Policy Gradients (ED2) method.
Missing: problems | Show results with:problems
Sep 7, 2024 · We conduct an empirical analysis of multiple tools from the RL toolbox in the continuous control setting and propose Ensemble Deep ...
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The combination of deep reinforcement learning (DRL) with ensemble methods has been proved to be highly effective in addressing complex sequential decision-.
Sep 6, 2024 · In this paper, we consider finding a novel but simple ensemble Deep RL algorithm to solve the resource consumption issue. Specifically, we ...
This paper proposes an ensemble-based DRL framework for wind farm control. An algorithm is proposed under the proposed framework to reduce the learning cost.
Sep 22, 2021 · In this paper, to avoid the notorious resources consumption issue, we design a novel and simple ensemble deep RL framework that integrates multiple models into ...
DDPG is a model-free, off-policy RL algorithm that adopts an actor-critic approach to solving continuous control problems in which the action space is ...