Copertina

Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lanier, Michael, Xu, Ying, Jacobs, Nathan, Zhang, Chongjie, Vorobeychik, Yevgeniy
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
di: Ge, Luise, et al.
Pubblicazione: (2025)

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

Verified Safe Reinforcement Learning for Neural Network Dynamic Models
di: Wu, Junlin, et al.
Pubblicazione: (2024)

A Scalable Approach to Solving Simulation-Based Network Security Games
di: Lanier, Michael, et al.
Pubblicazione: (2026)

Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks
di: Eghtesad, Taha, et al.
Pubblicazione: (2023)

Learning Linear Utility Functions From Pairwise Comparison Queries
di: Ge, Luise, et al.
Pubblicazione: (2024)

DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments
di: Sarkar, Anindya, et al.
Pubblicazione: (2026)

Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning
di: Lanier, Michael, et al.
Pubblicazione: (2026)

CoFineLLM: Conformal Finetuning of LLMs for Language-Instructed Robot Planning
di: Wang, Jun, et al.
Pubblicazione: (2025)

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

Attacks on Node Attributes in Graph Neural Networks
di: Xu, Ying, et al.
Pubblicazione: (2024)

Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning
di: Zhang, Hongming, et al.
Pubblicazione: (2023)

Active Geospatial Search for Efficient Tenant Eviction Outreach
di: Sarkar, Anindya, et al.
Pubblicazione: (2024)

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

Toward Learning POMDPs Beyond Full-Rank Actions and State Observability
di: Shaw, Seiji, et al.
Pubblicazione: (2026)

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

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

Hindsight Preference Replay Improves Preference-Conditioned Multi-Objective Reinforcement Learning
di: Shianifar, Jonaid, et al.
Pubblicazione: (2026)

Preference Poisoning Attacks on Reward Model Learning
di: Wu, Junlin, et al.
Pubblicazione: (2024)

GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
di: Sarkar, Anindya, et al.
Pubblicazione: (2024)

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

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

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

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

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

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

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

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

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

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

Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations
di: Hong, Joey, et al.
Pubblicazione: (2024)

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

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

Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
di: Yang, Rui, et al.
Pubblicazione: (2023)

HEAL: Hindsight Entropy-Assisted Learning for Reasoning Distillation
di: Zhang, Wenjing, et al.
Pubblicazione: (2026)

Human-Aware Robot Navigation via Reinforcement Learning with Hindsight Experience Replay and Curriculum Learning
di: Li, Keyu, et al.
Pubblicazione: (2021)

Guided Policy Optimization under Partial Observability
di: Li, Yueheng, et al.
Pubblicazione: (2025)

Solving Collaborative Dec-POMDPs with Deep Reinforcement Learning Heuristics
di: Soffair, Nitsan
Pubblicazione: (2022)

Scalable Policy-Based RL Algorithms for POMDPs
di: Anjarlekar, Ameya, et al.
Pubblicazione: (2025)

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