:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Min, Liu, Guanjun, Zhou, Ziyuan
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Artificial Intelligence
Accesso online:	https://arxiv.org/abs/2304.12653
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges
di: Zhou, Ziyuan, et al.
Pubblicazione: (2023)

SAJA: A State-Action Joint Attack Framework on Multi-Agent Deep Reinforcement Learning
di: Guo, Weiqi, et al.
Pubblicazione: (2025)

PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning
di: Guo, Weiran, et al.
Pubblicazione: (2025)

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

Recurrent Structural Policy Gradient for Partially Observable Mean Field Games
di: Wibault, Clarisse, et al.
Pubblicazione: (2026)

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

Causal Mean Field Multi-Agent Reinforcement Learning
di: Ma, Hao, et al.
Pubblicazione: (2025)

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making
di: Light, Jonathan, et al.
Pubblicazione: (2024)

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

GlobeDiff: State Diffusion Process for Partial Observability in Multi-Agent Systems
di: Yang, Yiqin, et al.
Pubblicazione: (2026)

Partially Observable Monte-Carlo Graph Search
di: You, Yang, et al.
Pubblicazione: (2025)

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations
di: Fu, Xiaolu, et al.
Pubblicazione: (2025)

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

Equivariant Reinforcement Learning under Partial Observability
di: Nguyen, Hai, et al.
Pubblicazione: (2024)

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

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

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

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

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

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

Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes
di: Tuyen, Le Pham, et al.
Pubblicazione: (2018)

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

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

Multi-Step First: A Lightweight Deep Reinforcement Learning Strategy for Robust Continuous Control with Partial Observability
di: Meng, Lingheng, et al.
Pubblicazione: (2022)

Achieving Equilibrium under Utility Heterogeneity: An Agent-Attention Framework for Multi-Agent Multi-Objective Reinforcement Learning
di: Li, Zhuhui, et al.
Pubblicazione: (2025)

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

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

Belief Memory: Agent Memory Under Partial Observability
di: Liao, Junfeng, et al.
Pubblicazione: (2026)

Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks
di: Liu, Qiong, et al.
Pubblicazione: (2024)

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

Temporal Knowledge-Graph Memory in a Partially Observable Environment
di: Kim, Taewoon, et al.
Pubblicazione: (2024)

Whispers in the Noise: Surrogate-Guided Concept Awakening via a Multi-Agent Framework
di: Sun, Mengyu, et al.
Pubblicazione: (2026)

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems
di: Ma, Yue, et al.
Pubblicazione: (2026)

Coordination Graphs for Constrained Multi-Agent Reinforcement Learning
di: Amaya-Corredor, Santiago, et al.
Pubblicazione: (2026)

Computing Universal Plans for Partially Observable Multi-Agent Routing Using Answer Set Programming
di: Zhu, Fengming, et al.
Pubblicazione: (2023)

Multi-Scenario Combination Based on Multi-Agent Reinforcement Learning to Optimize the Advertising Recommendation System
di: Zhao, Yang, et al.
Pubblicazione: (2024)

Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
di: Anand, Emile, et al.
Pubblicazione: (2024)

PrismAgent: Illuminating Harm in Memes via a Zero-Shot Interpretable Multi-Agent Framework
di: Ding, Zihan, et al.
Pubblicazione: (2026)

An Empirical Study on the Power of Future Prediction in Partially Observable Environments
di: Kwon, Jeongyeol, et al.
Pubblicazione: (2024)

Multi-Environment POMDPs: Discrete Model Uncertainty Under Partial Observability
di: Bovy, Eline M., et al.
Pubblicazione: (2025)