Copertina

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kiram, Firas Mohamed Elamine, Youkana, Imane, Saouli, Rachida, Susto, Gian Antonio, Kahloul, Laid
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
di: De Monte, Riccardo, et al.
Pubblicazione: (2026)

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

Exploiting Estimation Bias in Clipped Double Q-Learning for Continous Control Reinforcement Learning Tasks
di: Turcato, Niccolò, 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)

Reinforcement Learning for Durable Algorithmic Recourse
di: Ceccon, Marina, et al.
Pubblicazione: (2025)

Fully Dynamic Rebalancing in Dockless Bike-Sharing Systems via Deep Reinforcement Learning
di: Scarpel, Edoardo, et al.
Pubblicazione: (2026)

Edge Delayed Deep Deterministic Policy Gradient: efficient continuous control for edge scenarios
di: Sinigaglia, Alberto, et al.
Pubblicazione: (2024)

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)

Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
di: Sartor, Davide, et al.
Pubblicazione: (2025)

A Quantile Regression Approach for Remaining Useful Life Estimation with State Space Models
di: Frizzo, Davide, et al.
Pubblicazione: (2025)

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

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

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

A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement Learning
di: Cederle, Matteo, et al.
Pubblicazione: (2024)

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

Simple and Effective Specialized Representations for Fair Classifiers
di: Sinigaglia, Alberto, et al.
Pubblicazione: (2025)

Towards Explainable Anomaly Detection in Shared Mobility Systems
di: Isgandarov, Elnur, et al.
Pubblicazione: (2025)

Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning
di: Lanier, Michael, 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)

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

Real Time Human Detection by Unmanned Aerial Vehicles
di: Guettala, Walid, et al.
Pubblicazione: (2024)

Guided Policy Optimization under Partial Observability
di: Li, Yueheng, 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)

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

Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learning
di: Cederle, Matteo, et al.
Pubblicazione: (2026)

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability
di: Liu, Yushen, et al.
Pubblicazione: (2026)

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

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

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

ProDER: A Continual Learning Approach for Fault Prediction in Evolving Smart Grids
di: Efatinasab, Emad, et al.
Pubblicazione: (2025)

RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains
di: Ribeiro, João G., et al.
Pubblicazione: (2025)

Towards Transparent and Efficient Anomaly Detection in Industrial Processes through ExIFFI
di: Frizzo, Davide, et al.
Pubblicazione: (2024)

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

Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability
di: Kim, Taewoon, et al.
Pubblicazione: (2026)

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

Recurrent Reinforcement Learning with Memoroids
di: Morad, Steven, et al.
Pubblicazione: (2024)

Explainable Anomaly Detection for Electric Vehicles Charging Stations
di: Cederle, Matteo, et al.
Pubblicazione: (2025)

Towards Model-Free Learning in Dynamic Population Games: An Application to Karma Economies
di: Cederle, Matteo, et al.
Pubblicazione: (2026)

Torch-Uncertainty: A Deep Learning Framework for Uncertainty Quantification
di: Lafage, Adrien, et al.
Pubblicazione: (2025)