Web18 de mar. de 2024 · Afterward, a neural network-based actor-critic structure is built for approximating the iterative control policies and value functions. Finally, a large-scale formation control problem is provided to demonstrate the performance of our developed hierarchical leader-following formation control structure and MsGPI algorithm.
Curious Hierarchical Actor-Critic Reinforcement Learning
WebThis article studies the hierarchical sliding-mode surface (HSMS)-based adaptive optimal control problem for a class of switched continuous-time (CT) nonlinear systems with unknown perturbation under an actor-critic (AC) neural networks (NNs) architecture. First, a novel perturbation observer with a … Web11 de abr. de 2024 · Actor-critic algorithms are a popular class of reinforcement learning methods that combine the advantages of value-based and policy-based approaches. … list of idaho colleges
Curious Hierarchical Actor-Critic Reinforcement Learning
Web4 de set. de 2024 · To address this problem, we had analyzed the newest existing framework, Hierarchical Actor-Critic with Hindsight (HAC), test it in the simulated mobile robot environment and determine the optimal configuration of parameters and ways to encode information about the environment states. Keywords. Hierarchical Actor-Critic; … Web7 de mai. de 2024 · Curious Hierarchical Actor-Critic Reinforcement Learning. Hierarchical abstraction and curiosity-driven exploration are two common paradigms in current reinforcement learning approaches to break down difficult problems into a sequence of simpler ones and to overcome reward sparsity. However, there is a lack of approaches … Web25 de ago. de 2024 · Reinforcement Learning From Hierarchical Critics. Abstract: In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of reinforcement learning (RL) in competition tasks. Within the framework of actor–critic RL, we introduce multiple cooperative critics from two … imax theater donation request