Hierarchical Reinforcement Learning
87 papers with code • 0 benchmarks • 2 datasets
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Multi-Session Budget Optimization for Forward Auction-based Federated Learning
Based on hierarchical reinforcement learning, MultiBOS-AFL jointly optimizes inter-session budget pacing and intra-session bidding for AFL MUs, with the objective of maximizing the total utility.
Imagination-Augmented Hierarchical Reinforcement Learning for Safe and Interactive Autonomous Driving in Urban Environments
Modern HRL typically designs a hierarchical agent composed of a high-level policy and low-level policies.
A Central Motor System Inspired Pre-training Reinforcement Learning for Robotic Control
Designing controllers to achieve natural motor capabilities for multi-joint robots is a significant challenge.
Rethinking Decision Transformer via Hierarchical Reinforcement Learning
Decision Transformer (DT) is an innovative algorithm leveraging recent advances of the transformer architecture in reinforcement learning (RL).
MTAC: Hierarchical Reinforcement Learning-based Multi-gait Terrain-adaptive Quadruped Controller
Urban search and rescue missions require rapid first response to minimize loss of life and damage.
Learning Extrinsic Dexterity with Parameterized Manipulation Primitives
We solve this problem by learning a sequence of actions that utilize the environment to change the object's pose.
Forecaster: Towards Temporally Abstract Tree-Search Planning from Pixels
The ability to plan at many different levels of abstraction enables agents to envision the long-term repercussions of their decisions and thus enables sample-efficient learning.
Hierarchical Reinforcement Learning for Temporal Pattern Prediction
In this work, we explore the use of hierarchical reinforcement learning (HRL) for the task of temporal sequence prediction.
Safe Hierarchical Reinforcement Learning for CubeSat Task Scheduling Based on Energy Consumption
This paper presents a Hierarchical Reinforcement Learning methodology tailored for optimizing CubeSat task scheduling in Low Earth Orbits (LEO).
Hierarchical reinforcement learning with natural language subgoals
Hierarchical reinforcement learning has been a compelling approach for achieving goal directed behavior over long sequences of actions.