Cover Image

Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Hongming, Ren, Tongzheng, Xiao, Chenjun, Schuurmans, Dale, Dai, Bo
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Spectral Representation-based Reinforcement Learning
by: Gao, Chenxiao, et al.
Published: (2025)

Diffusion Spectral Representation for Reinforcement Learning
by: Shribak, Dmitry, et al.
Published: (2024)

$β$-DQN: Improving Deep Q-Learning By Evolving the Behavior
by: Zhang, Hongming, et al.
Published: (2025)

Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
by: Lu, Miao, et al.
Published: (2022)

Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
by: Che, Fengdi, et al.
Published: (2024)

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
by: Yue, Bo, et al.
Published: (2024)

Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability
by: Luis, Carlos E., et al.
Published: (2024)

Beyond Expectations: Learning with Stochastic Dominance Made Practical
by: Cen, Shicong, et al.
Published: (2024)

Multi-View Causal Representation Learning with Partial Observability
by: Yao, Dingling, et al.
Published: (2023)

Hindsight Preference Learning for Offline Preference-based Reinforcement Learning
by: Gao, Chen-Xiao, et al.
Published: (2024)

Zero-Shot Reinforcement Learning Under Partial Observability
by: Jeen, Scott, et al.
Published: (2025)

Near-Optimal Partially Observable Reinforcement Learning with Partial Online State Information
by: Shi, Ming, et al.
Published: (2023)

A Sparsity Principle for Partially Observable Causal Representation Learning
by: Xu, Danru, et al.
Published: (2024)

Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning
by: Lanier, Michael, et al.
Published: (2024)

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability
by: Kiram, Firas Mohamed Elamine, et al.
Published: (2026)

Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
by: Zhao, Yike, et al.
Published: (2026)

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
by: Gao, Chen-Xiao, et al.
Published: (2025)

Spectral Ghost in Representation Learning: from Component Analysis to Self-Supervised Learning
by: Dai, Bo, et al.
Published: (2026)

Benchmarking Partial Observability in Reinforcement Learning with a Suite of Memory-Improvable Domains
by: Tao, Ruo Yu, et al.
Published: (2025)

Belief States for Cooperative Multi-Agent Reinforcement Learning under Partial Observability
by: Pritz, Paul J., et al.
Published: (2025)

On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
by: Altabaa, Awni, et al.
Published: (2024)

A Convolution and Attention Based Encoder for Reinforcement Learning under Partial Observability
by: Wang, Wuhao, et al.
Published: (2025)

Representation Learning via Non-Contrastive Mutual Information
by: Guo, Zhaohan Daniel, et al.
Published: (2025)

Learning to Focus: Prioritizing Informative Histories with Structured Attention Mechanisms in Partially Observable Reinforcement Learning
by: Allegue, Daniel De Dios, et al.
Published: (2025)

Transformer-Based Reinforcement Learning for Autonomous Orbital Collision Avoidance in Partially Observable Environments
by: Georges, Thomas, et al.
Published: (2026)

Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes
by: Vora, Kevin, et al.
Published: (2025)

Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments
by: Dedieu, Antoine, et al.
Published: (2024)

A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning
by: Zhang, Hongming, et al.
Published: (2021)

Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
by: Cen, Shicong, et al.
Published: (2024)

Provably Efficient Action-Manipulation Attack Against Continuous Reinforcement Learning
by: Luo, Zhi, et al.
Published: (2024)

Embed to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency
by: Wang, Lingxiao, et al.
Published: (2022)

An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models
by: Pan, Yangchen, et al.
Published: (2024)

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
by: Lang, Leon, et al.
Published: (2024)

Online Feedback Efficient Active Target Discovery in Partially Observable Environments
by: Sarkar, Anindya, et al.
Published: (2025)

Symmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist
by: Nguyen, Hai, et al.
Published: (2024)

Provable Partially Observable Reinforcement Learning with Privileged Information
by: Cai, Yang, et al.
Published: (2024)

Exploring and Benchmarking the Planning Capabilities of Large Language Models
by: Bohnet, Bernd, et al.
Published: (2024)

Provably Efficient Partially Observable Risk-Sensitive Reinforcement Learning with Hindsight Observation
by: Zhang, Tonghe, et al.
Published: (2024)

Soft Preference Optimization: Aligning Language Models to Expert Distributions
by: Sharifnassab, Arsalan, et al.
Published: (2024)

Efficient Preference-based Reinforcement Learning via Aligned Experience Estimation
by: Bai, Fengshuo, et al.
Published: (2024)