Imagen de Portada

Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Arana-Catania, Miguel, Guo, Weisi
Formato:	Preprint
Publicado:	2025
Materias:	Robotics Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Wind Estimation in Unmanned Aerial Vehicles with Causal Machine Learning
por: Alwalan, Abdulaziz, et al.
Publicado: (2024)

Causal Reinforcement Learning for Optimisation of Robot Dynamics in Unknown Environments
por: Dcruz, Julian Gerald, et al.
Publicado: (2024)

Autonomous Robotic Arm Manipulation for Planetary Missions using Causal Machine Learning
por: McDonnell, C., et al.
Publicado: (2024)

Spacecraft inertial parameters estimation using time series clustering and reinforcement learning
por: Platanitis, Konstantinos, et al.
Publicado: (2024)

Incorporating System-level Safety Requirements in Perception Models via Reinforcement Learning
por: Fan, Weisi, et al.
Publicado: (2024)

A causal learning approach to in-orbit inertial parameter estimation for multi-payload deployers
por: Platanitis, Konstantinos, et al.
Publicado: (2025)

Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability
por: Liu, Zihao, et al.
Publicado: (2025)

Benchmarking Deep Reinforcement Learning for Navigation in Denied Sensor Environments
por: Wisniewski, Mariusz, et al.
Publicado: (2024)

Dynamic Neural Curiosity Enhances Learning Flexibility for Autonomous Goal Discovery
por: Houbre, Quentin, et al.
Publicado: (2024)

Multiagent Reinforcement Learning with Neighbor Action Estimation
por: Luo, Zhenglong, et al.
Publicado: (2026)

Reinforcement Learning for Optimal Experiment Design in Parameter Identification of Mechatronic Systems
por: Langschwert, Julian, et al.
Publicado: (2026)

Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning
por: So, Oswin, et al.
Publicado: (2026)

Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
por: Pan, Yiyuan, et al.
Publicado: (2025)

Neural Motion Simulator: Pushing the Limit of World Models in Reinforcement Learning
por: Hao, Chenjie, et al.
Publicado: (2025)

Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement Learning
por: Corsi, Davide, et al.
Publicado: (2024)

High-Performance Reinforcement Learning on Spot: Optimizing Simulation Parameters with Distributional Measures
por: Miller, AJ, et al.
Publicado: (2025)

ROPES: Robotic Pose Estimation via Score-Based Causal Representation Learning
por: Kulkarni, Pranamya, et al.
Publicado: (2025)

CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening
por: Kulkarni, Amar, et al.
Publicado: (2024)

Causal Flow Q-Learning for Robust Offline Reinforcement Learning
por: Li, Mingxuan, et al.
Publicado: (2026)

Hierarchical Reinforcement Learning for Safe Mapless Navigation with Congestion Estimation
por: Gao, Jianqi, et al.
Publicado: (2025)

Cost Function Estimation Using Inverse Reinforcement Learning with Minimal Observations
por: Mehrdad, Sarmad, et al.
Publicado: (2025)

Estimator-Coupled Reinforcement Learning for Robust Purely Tactile In-Hand Manipulation
por: Röstel, Lennart, et al.
Publicado: (2023)

EnCoMP: Enhanced Covert Maneuver Planning with Adaptive Threat-Aware Visibility Estimation using Offline Reinforcement Learning
por: Hossain, Jumman, et al.
Publicado: (2024)

Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning
por: Schneider, Lukas, et al.
Publicado: (2023)

MoRe-ERL: Learning Motion Residuals using Episodic Reinforcement Learning
por: Huang, Xi, et al.
Publicado: (2025)

Accelerating Residual Reinforcement Learning with Uncertainty Estimation
por: Dodeja, Lakshita, et al.
Publicado: (2025)

Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning
por: Bøhn, Eivind, et al.
Publicado: (2021)

Estimating the Joint Probability of Scenario Parameters with Gaussian Mixture Copula Models
por: Reichenbächer, Christian, et al.
Publicado: (2025)

Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving
por: Lin, Haohong, et al.
Publicado: (2023)

Extensive Exploration in Complex Traffic Scenarios using Hierarchical Reinforcement Learning
por: Zhang, Zhihao, et al.
Publicado: (2025)

Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
por: Celik, Onur, et al.
Publicado: (2024)

Agile Interception of a Flying Target using Competitive Reinforcement Learning
por: Gavin, Timothée, et al.
Publicado: (2026)

Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient
por: Wang, Wenlong, et al.
Publicado: (2024)

Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception
por: Liu, Yandi, et al.
Publicado: (2025)

Accelerating Model-Based Reinforcement Learning using Non-Linear Trajectory Optimization
por: Calì, Marco, et al.
Publicado: (2025)

Zero-Shot Policy Transfer in Reinforcement Learning using Buckingham's Pi Theorem
por: Pascoa, Francisco, et al.
Publicado: (2025)

Path Following and Stabilisation of a Bicycle Model using a Reinforcement Learning Approach
por: Weyrer, Sebastian, et al.
Publicado: (2024)

MPC-based Deep Reinforcement Learning Method for Space Robotic Control with Fuel Sloshing Mitigation
por: Ramezani, Mahya, et al.
Publicado: (2025)

Equivariant Offline Reinforcement Learning
por: Tangri, Arsh, et al.
Publicado: (2024)

Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks
por: Pandaram, Muthukumar, et al.
Publicado: (2025)