Imagen de Portada

Learning Safe Numeric Planning Action Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Mordoch, Argaman, Shperberg, Shahaf S., Stern, Roni, Juba, Berndan
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Integrating Reinforcement Learning, Action Model Learning, and Numeric Planning for Tackling Complex Tasks
por: Benyamin, Yarin, et al.
Publicado: (2025)

RAMP: Hybrid DRL for Online Learning of Numeric Action Models
por: Benyamin, Yarin, et al.
Publicado: (2026)

Toward PDDL Planning Copilot
por: Benyamin, Yarin, et al.
Publicado: (2025)

Safe Learning of PDDL Domains with Conditional Effects -- Extended Version
por: Mordoch, Argaman, et al.
Publicado: (2024)

EvoGPT: Leveraging LLM-Driven Seed Diversity to Improve Search-Based Test Suite Generation
por: Broide, Lior, et al.
Publicado: (2025)

A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks
por: Agostinelli, Forest, et al.
Publicado: (2021)

From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution
por: Erez, Lidor, et al.
Publicado: (2026)

Beyond Single-Step Updates: Reinforcement Learning of Heuristics with Limited-Horizon Search
por: Hadar, Gal, et al.
Publicado: (2025)

Skill-based Safe Reinforcement Learning with Risk Planning
por: Zhang, Hanping, et al.
Publicado: (2025)

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

CAPSULE: Control-Theoretic Action Perturbations for Safe Uncertainty-Aware Reinforcement Learning
por: Narava, Rahul, et al.
Publicado: (2026)

Differentiable Learning of Lifted Action Schemas for Classical Planning
por: Reiter, Jonas, et al.
Publicado: (2026)

PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
por: Zitouni, Abdelkrim, et al.
Publicado: (2025)

Equivariant Action Sampling for Reinforcement Learning and Planning
por: Zhao, Linfeng, et al.
Publicado: (2024)

Planning and Acting While the Clock Ticks
por: Coles, Andrew, et al.
Publicado: (2024)

C-MCTS: Safe Planning with Monte Carlo Tree Search
por: Parthasarathy, Dinesh, et al.
Publicado: (2023)

On Parallel External-Memory Bidirectional Search
por: Siag, Lior, et al.
Publicado: (2024)

KL-regularization Itself is Differentially Private in Bandits and RLHF
por: Zhang, Yizhou, et al.
Publicado: (2025)

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction
por: Durkin, Alex, et al.
Publicado: (2025)

Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning
por: Banerjee, Arko, et al.
Publicado: (2024)

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

SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning
por: Anisimov, Maksim, et al.
Publicado: (2026)

The Global Neural World Model: Spatially Grounded Discrete Topologies for Action-Conditioned Planning
por: Kermiche, Noureddine
Publicado: (2026)

Safe Flow Q-Learning: Offline Safe Reinforcement Learning with Reachability-Based Flow Policies
por: Tayal, Mumuksh, et al.
Publicado: (2026)

Advancing Safe Mechanical Ventilation Using Offline RL With Hybrid Actions and Clinically Aligned Rewards
por: Yousuf, Muhammad Hamza, et al.
Publicado: (2025)

Improving planning and MBRL with temporally-extended actions
por: Chatterjee, Palash, et al.
Publicado: (2025)

Reinforcement Learning by Guided Safe Exploration
por: Yang, Qisong, et al.
Publicado: (2023)

Probabilistic Shielding for Safe Reinforcement Learning
por: Court, Edwin Hamel-De le, et al.
Publicado: (2025)

Safe RLHF-V: Safe Reinforcement Learning from Multi-modal Human Feedback
por: Ji, Jiaming, et al.
Publicado: (2025)

SafeMIL: Learning Offline Safe Imitation Policy from Non-Preferred Trajectories
por: Burnwal, Returaj, et al.
Publicado: (2025)

FAME: Formal Abstract Minimal Explanation for Neural Networks
por: Boumazouza, Ryma, et al.
Publicado: (2026)

Bidirectional Bounded-Suboptimal Heuristic Search with Consistent Heuristics
por: Shperberg, Shahaf S., et al.
Publicado: (2025)

DAWM: Diffusion Action World Models for Offline Reinforcement Learning via Action-Inferred Transitions
por: Li, Zongyue, et al.
Publicado: (2025)

Model-based Reinforcement Learning for Parameterized Action Spaces
por: Zhang, Renhao, et al.
Publicado: (2024)

What Do Latent Action Models Actually Learn?
por: Zhang, Chuheng, et al.
Publicado: (2025)

Comparative Analysis of Parameterized Action Actor-Critic Reinforcement Learning Algorithms for Web Search Match Plan Generation
por: Bapoo, Ubayd, et al.
Publicado: (2025)

Implicit Safe Set Algorithm for Provably Safe Reinforcement Learning
por: Zhao, Weiye, et al.
Publicado: (2024)

Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning
por: Liang, Jinhao, et al.
Publicado: (2025)

Differentially Private Data Release on Graphs: Inefficiencies and Unfairness
por: Fioretto, Ferdinando, et al.
Publicado: (2024)

Online Optimization for Offline Safe Reinforcement Learning
por: Chemingui, Yassine, et al.
Publicado: (2025)