Cover Image

Incorporating Spatial Information into Goal-Conditioned Hierarchical Reinforcement Learning via Graph Representations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Shuyuan, Wang, Zihan, Chang, Xiao-Wen, Precup, Doina
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Partial Models for Building Adaptive Model-Based Reinforcement Learning Agents
by: Alver, Safa, et al.
Published: (2024)

Parseval Regularization for Continual Reinforcement Learning
by: Chung, Wesley, et al.
Published: (2024)

Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
by: Arnob, Samin Yeasar, et al.
Published: (2025)

Fluid-Agent Reinforcement Learning
by: Sharma, Shishir, et al.
Published: (2026)

Diversity-Enriched Option-Critic
by: Kamat, Anand, et al.
Published: (2020)

Functional Acceleration for Policy Mirror Descent
by: Chelu, Veronica, et al.
Published: (2024)

A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings
by: Alver, Safa, et al.
Published: (2022)

Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems
by: Carr, Jonathan Colaço, et al.
Published: (2026)

Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments
by: Luo, Ziyan, et al.
Published: (2025)

SCAR: Shapley Credit Assignment for More Efficient RLHF
by: Cao, Meng, et al.
Published: (2025)

Proposing Hierarchical Goal-Conditioned Policy Planning in Multi-Goal Reinforcement Learning
by: Rens, Gavin B.
Published: (2025)

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
by: Zhao, Mingde, et al.
Published: (2023)

More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling
by: Ishfaq, Haque, et al.
Published: (2024)

Adaptive Exploration for Data-Efficient General Value Function Evaluations
by: Jain, Arushi, et al.
Published: (2024)

Data-Efficient Hierarchical Goal-Conditioned Reinforcement Learning via Normalizing Flows
by: Garg, Shaswat, et al.
Published: (2026)

Capacity-Constrained Continual Learning
by: Wen, Zheng, et al.
Published: (2025)

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
by: Chuck, Caleb, et al.
Published: (2025)

Goal Exploration via Adaptive Skill Distribution for Goal-Conditioned Reinforcement Learning
by: Wu, Lisheng, et al.
Published: (2024)

Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations
by: Cunegatti, Elia, et al.
Published: (2023)

Abstraction for Offline Goal-Conditioned Reinforcement Learning
by: Wibault, Clarisse, et al.
Published: (2026)

SVL: Goal-Conditioned Reinforcement Learning as Survival Learning
by: Tiofack, Franki Nguimatsia, et al.
Published: (2026)

GCHR : Goal-Conditioned Hindsight Regularization for Sample-Efficient Reinforcement Learning
by: Lei, Xing, et al.
Published: (2025)

Policy Gradient Methods in the Presence of Symmetries and State Abstractions
by: Panangaden, Prakash, et al.
Published: (2023)

Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
by: Patil, Gandharv, et al.
Published: (2022)

Goal-Conditioned Reinforcement Learning for Data-Driven Maritime Navigation
by: Vaidheeswaran, Vaishnav, et al.
Published: (2025)

Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
by: Choi, Jinwoo, et al.
Published: (2026)

SMORE: Score Models for Offline Goal-Conditioned Reinforcement Learning
by: Sikchi, Harshit, et al.
Published: (2023)

Decoupled Hierarchical Reinforcement Learning with State Abstraction for Discrete Grids
by: Xiao, Qingyu, et al.
Published: (2025)

Goal-Conditioned Data Augmentation for Offline Reinforcement Learning
by: Huang, Xingshuai, et al.
Published: (2024)

Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
by: McCracken, Gavin, et al.
Published: (2025)

Why Goal-Conditioned Reinforcement Learning Works: Relation to Dual Control
by: Lawrence, Nathan P., et al.
Published: (2025)

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
by: Feng, Xinsong, et al.
Published: (2025)

TLDR: Unsupervised Goal-Conditioned RL via Temporal Distance-Aware Representations
by: Bae, Junik, et al.
Published: (2024)

Rotation-Preserving Supervised Fine-Tuning
by: Jin, Hangzhan, et al.
Published: (2026)

Option-aware Temporally Abstracted Value for Offline Goal-Conditioned Reinforcement Learning
by: Ahn, Hongjoon, et al.
Published: (2025)

Reconciling Spatial and Temporal Abstractions for Goal Representation
by: Zadem, Mehdi, et al.
Published: (2024)

Probabilistic Subgoal Representations for Hierarchical Reinforcement learning
by: Wang, Vivienne Huiling, et al.
Published: (2024)

Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning
by: Duan, Yuanlin, et al.
Published: (2024)

Planner-Admissible Graph-PDE Value Extensions for Sparse Goal-Conditioned Planning
by: Zhang, Shiheng
Published: (2026)

Goal Recognition as Reinforcement Learning
by: Amado, Leonardo Rosa, et al.
Published: (2022)