Cover Image

Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Riscos, Pablo de los, Corbacho, Fernando J.
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Machine Learning I.2.6; I.2.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
by: Núñez-Molina, Carlos, et al.
Published: (2023)

CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
by: Sauter, Andreas W. M., et al.
Published: (2024)

Learning to Select Goals in Automated Planning with Deep-Q Learning
by: Núñez-Molina, Carlos, et al.
Published: (2024)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
by: Aichmüller, Michael, et al.
Published: (2024)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
by: Wang, Yuxuan, et al.
Published: (2025)

What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
by: Zhang, Xinyu
Published: (2026)

LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
by: George, Robert Joseph, et al.
Published: (2025)

Constrained Auto-Bidding via Generative Response Modeling
by: Yang, Eunseok, et al.
Published: (2026)

Autonomous Decision Making for UAV Cooperative Pursuit-Evasion Game with Reinforcement Learning
by: Zhao, Yang, et al.
Published: (2024)

Predicting Future Actions of Reinforcement Learning Agents
by: Chung, Stephen, et al.
Published: (2024)

Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
by: Kang, Jiyeon, et al.
Published: (2025)

Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning
by: Wang, Zizhao, et al.
Published: (2024)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

Adaptable Hindsight Experience Replay for Search-Based Learning
by: Vazaios, Alexandros, et al.
Published: (2025)

The Shortcomings of Force-from-Motion in Robot Learning
by: Aljalbout, Elie, et al.
Published: (2024)

Differentiable Symbolic Planning: A Neural Architecture for Constraint Reasoning with Learned Feasibility
by: Oruganti, Venkatakrishna Reddy
Published: (2026)

Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
by: Nuzhin, Egor E., et al.
Published: (2024)

GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
by: Hiremath, Prakul Sunil
Published: (2026)

From Next Token Prediction to (STRIPS) World Models
by: Núñez-Molina, Carlos, et al.
Published: (2025)

Sim-to-reality adaptation for Deep Reinforcement Learning applied to an underwater docking application
by: Chaarani, Alaaeddine, et al.
Published: (2026)

Learning, Fast and Slow: Towards LLMs That Adapt Continually
by: Tiwari, Rishabh, et al.
Published: (2026)

Procedural Game Level Design with Deep Reinforcement Learning
by: Özkan, Miraç Buğra
Published: (2025)

On the Limits of Learned Importance Scoring for KV Cache Compression
by: Steele, Brady
Published: (2026)

PIRS: Physics-Informed Reward Shaping for SAC-Based Building Energy Management
by: Zaregarizi, Shadmehr, et al.
Published: (2026)

A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making
by: Núñez-Molina, Carlos, et al.
Published: (2023)

Active Causal Experimentalist (ACE): Learning Intervention Strategies via Direct Preference Optimization
by: Cooper, Patrick, et al.
Published: (2026)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)

Improving Industrial Injection Molding Processes with Explainable AI for Quality Classification
by: Rottenwalter, Georg, et al.
Published: (2025)

Novel Approaches to Artificial Intelligence Development Based on the Nearest Neighbor Method
by: Priezzhev, I. I., et al.
Published: (2025)

Advancements in synthetic data extraction for industrial injection molding
by: Rottenwalter, Georg, et al.
Published: (2025)

Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models
by: Raman, Vishal, et al.
Published: (2025)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

The State of Robot Motion Generation
by: Bekris, Kostas E., et al.
Published: (2024)

Foundational Requirements for Artificial General Intelligence: A Falsifiable Framework Based on Signal Prediction
by: Šprogar, Matej
Published: (2025)

Embedded Safety-Aligned Intelligence via Differentiable Internal Alignment Embeddings
by: Rathva, Harsh, et al.
Published: (2025)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
by: Zawalski, Michał, et al.
Published: (2022)

Inverting Cryptographic Hash Functions via Cube-and-Conquer
by: Zaikin, Oleg
Published: (2022)

Bridging the Reasoning Gap: Small LLMs Can Plan with Generalised Strategies
by: Borro, Andrey, et al.
Published: (2025)

Incentives for Responsiveness, Instrumental Control and Impact
by: Carey, Ryan, et al.
Published: (2020)