Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
Fuente:
arXiv
Guardado en:
| Autores principales: | Nuzhin, Egor E., Brilliantov, Nikolai V. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
por: Yousaf, Iqra
Publicado: (2024)
por: Yousaf, Iqra
Publicado: (2024)
Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
por: Aichmüller, Michael, et al.
Publicado: (2024)
por: Aichmüller, Michael, et al.
Publicado: (2024)
Safe Reinforcement Learning with Preference-based Constraint Inference
por: Li, Chenglin, et al.
Publicado: (2026)
por: Li, Chenglin, et al.
Publicado: (2026)
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
por: Sauter, Andreas W. M., et al.
Publicado: (2024)
por: Sauter, Andreas W. M., et al.
Publicado: (2024)
GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
por: Hiremath, Prakul Sunil
Publicado: (2026)
por: Hiremath, Prakul Sunil
Publicado: (2026)
A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
por: Wang, Yuxuan, et al.
Publicado: (2025)
por: Wang, Yuxuan, et al.
Publicado: (2025)
Learning to Select Goals in Automated Planning with Deep-Q Learning
por: Núñez-Molina, Carlos, et al.
Publicado: (2024)
por: Núñez-Molina, Carlos, et al.
Publicado: (2024)
Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
por: Silue, Bram, et al.
Publicado: (2025)
por: Silue, Bram, et al.
Publicado: (2025)
What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
por: Zhang, Xinyu
Publicado: (2026)
por: Zhang, Xinyu
Publicado: (2026)
Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
por: Riscos, Pablo de los, et al.
Publicado: (2024)
por: Riscos, Pablo de los, et al.
Publicado: (2024)
SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
por: Vincze, Mátyás, et al.
Publicado: (2024)
por: Vincze, Mátyás, et al.
Publicado: (2024)
NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
por: Núñez-Molina, Carlos, et al.
Publicado: (2023)
por: Núñez-Molina, Carlos, et al.
Publicado: (2023)
Adaptable Hindsight Experience Replay for Search-Based Learning
por: Vazaios, Alexandros, et al.
Publicado: (2025)
por: Vazaios, Alexandros, et al.
Publicado: (2025)
Differentiable Symbolic Planning: A Neural Architecture for Constraint Reasoning with Learned Feasibility
por: Oruganti, Venkatakrishna Reddy
Publicado: (2026)
por: Oruganti, Venkatakrishna Reddy
Publicado: (2026)
Predicting Future Actions of Reinforcement Learning Agents
por: Chung, Stephen, et al.
Publicado: (2024)
por: Chung, Stephen, et al.
Publicado: (2024)
Social Interpretable Reinforcement Learning
por: Custode, Leonardo Lucio, et al.
Publicado: (2024)
por: Custode, Leonardo Lucio, et al.
Publicado: (2024)
Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
por: Wang, Zizhao, et al.
Publicado: (2024)
por: Wang, Zizhao, et al.
Publicado: (2024)
LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
por: George, Robert Joseph, et al.
Publicado: (2025)
por: George, Robert Joseph, et al.
Publicado: (2025)
Constrained Auto-Bidding via Generative Response Modeling
por: Yang, Eunseok, et al.
Publicado: (2026)
por: Yang, Eunseok, et al.
Publicado: (2026)
Embedded Safety-Aligned Intelligence via Differentiable Internal Alignment Embeddings
por: Rathva, Harsh, et al.
Publicado: (2025)
por: Rathva, Harsh, et al.
Publicado: (2025)
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
por: Zawalski, Michał, et al.
Publicado: (2022)
por: Zawalski, Michał, et al.
Publicado: (2022)
Incentives for Responsiveness, Instrumental Control and Impact
por: Carey, Ryan, et al.
Publicado: (2020)
por: Carey, Ryan, et al.
Publicado: (2020)
Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
por: Kang, Jiyeon, et al.
Publicado: (2025)
por: Kang, Jiyeon, et al.
Publicado: (2025)
Regret-Aware Policy Optimization: Environment-Level Memory for Replay Suppression under Delayed Harm
por: Hiremath, Prakul Sunil
Publicado: (2026)
por: Hiremath, Prakul Sunil
Publicado: (2026)
On the Generalization Gap in LLM Planning: Tests and Verifier-Reward RL
por: Belcamino, Valerio, et al.
Publicado: (2026)
por: Belcamino, Valerio, et al.
Publicado: (2026)
Not All Transitions Matter: Evidence from PPO
por: Basnet, Ajhesh
Publicado: (2026)
por: Basnet, Ajhesh
Publicado: (2026)
AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites
por: Zhang, Qinshi, et al.
Publicado: (2026)
por: Zhang, Qinshi, et al.
Publicado: (2026)
SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
por: Mishra, Satyam, et al.
Publicado: (2025)
por: Mishra, Satyam, et al.
Publicado: (2025)
On the Limits of Learned Importance Scoring for KV Cache Compression
por: Steele, Brady
Publicado: (2026)
por: Steele, Brady
Publicado: (2026)
Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
por: Pawar, Urvi, et al.
Publicado: (2025)
por: Pawar, Urvi, et al.
Publicado: (2025)
Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
por: Chapman, James, et al.
Publicado: (2025)
por: Chapman, James, et al.
Publicado: (2025)
From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
por: Tomashevskiy, Timofey
Publicado: (2026)
por: Tomashevskiy, Timofey
Publicado: (2026)
Sim-to-reality adaptation for Deep Reinforcement Learning applied to an underwater docking application
por: Chaarani, Alaaeddine, et al.
Publicado: (2026)
por: Chaarani, Alaaeddine, et al.
Publicado: (2026)
FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
por: Pivezhandi, Mohammad, et al.
Publicado: (2024)
por: Pivezhandi, Mohammad, et al.
Publicado: (2024)
Combining Trained Models in Reinforcement Learning
por: Patil, Ujjwal, et al.
Publicado: (2026)
por: Patil, Ujjwal, et al.
Publicado: (2026)
Procedural Game Level Design with Deep Reinforcement Learning
por: Özkan, Miraç Buğra
Publicado: (2025)
por: Özkan, Miraç Buğra
Publicado: (2025)
Resolving Action Bottleneck: Agentic Reinforcement Learning Informed by Token-Level Energy
por: He, Langzhou, et al.
Publicado: (2026)
por: He, Langzhou, et al.
Publicado: (2026)
SCULPT: Constraint-Guided Pruned MCTS that Carves Efficient Paths for Mathematical Reasoning
por: Fang, Qitong, et al.
Publicado: (2026)
por: Fang, Qitong, et al.
Publicado: (2026)
Scaling Trends for Multi-Hop Contextual Reasoning in Mid-Scale Language Models
por: Steele, Brady, et al.
Publicado: (2026)
por: Steele, Brady, et al.
Publicado: (2026)
The ARC of Progress towards AGI: A Living Survey of Abstraction and Reasoning
por: Vahdati, Sahar, et al.
Publicado: (2026)
por: Vahdati, Sahar, et al.
Publicado: (2026)
Ejemplares similares
-
AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
por: Yousaf, Iqra
Publicado: (2024) -
Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
por: Aichmüller, Michael, et al.
Publicado: (2024) -
Safe Reinforcement Learning with Preference-based Constraint Inference
por: Li, Chenglin, et al.
Publicado: (2026) -
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
por: Sauter, Andreas W. M., et al.
Publicado: (2024) -
GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
por: Hiremath, Prakul Sunil
Publicado: (2026)