Imagen de Portada

From model-based learning to model-free behaviour with Meta-Interpretive Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Patsantzis, Stassa
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Self-Supervised Inductive Logic Programming
por: Patsantzis, Stassa
Publicado: (2025)

Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning
por: Champion, Théophile, et al.
Publicado: (2024)

Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm
por: Renard, Titouan, et al.
Publicado: (2024)

Meta Additive Model: Interpretable Sparse Learning With Auto Weighting
por: Zhang, Xuelin, et al.
Publicado: (2026)

Causal prompting model-based offline reinforcement learning
por: Yu, Xuehui, et al.
Publicado: (2024)

Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model
por: Moen, Hans, et al.
Publicado: (2024)

Interpretable experiential learning based on state history and global feedback
por: Kolonin, Anton
Publicado: (2026)

Policy-shaped prediction: avoiding distractions in model-based reinforcement learning
por: Hutson, Miles, et al.
Publicado: (2024)

Set-based Meta-Interpolation for Few-Task Meta-Learning
por: Lee, Seanie, et al.
Publicado: (2022)

Generative method for aerodynamic optimization based on classifier-free guided denoising diffusion probabilistic model
por: Deng, Shisong, et al.
Publicado: (2025)

Extreme value forecasting using relevance-based data augmentation with deep learning models
por: Hua, Junru, et al.
Publicado: (2025)

Acting upon Imagination: when to trust imagined trajectories in model based reinforcement learning
por: Remonda, Adrian, et al.
Publicado: (2021)

Sophisticated Learning: A novel algorithm for active learning during model-based planning
por: Hodson, Rowan, et al.
Publicado: (2023)

ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations
por: Fonseca, Joao, et al.
Publicado: (2026)

VRAIL: Vectorized Reward-based Attribution for Interpretable Learning
por: Kim, Jina, et al.
Publicado: (2025)

Towards Case-based Interpretability for Medical Federated Learning
por: Latorre, Laura, et al.
Publicado: (2024)

Meta-learning in healthcare: A survey
por: Rafiei, Alireza, et al.
Publicado: (2023)

A Meta-learning based Stacked Regression Approach for Customer Lifetime Value Prediction
por: Gadgil, Karan, et al.
Publicado: (2023)

What model does MuZero learn?
por: He, Jinke, et al.
Publicado: (2023)

Robust agents learn causal world models
por: Richens, Jonathan, et al.
Publicado: (2024)

A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning
por: Zhang, Xiaojin, et al.
Publicado: (2023)

InFusionLayer: a CFA-based ensemble tool to generate new classifiers for learning and modeling
por: Roginek, Eric, et al.
Publicado: (2026)

Efficiency optimization of large-scale language models based on deep learning in natural language processing tasks
por: Mei, Taiyuan, et al.
Publicado: (2024)

A Bayesian explanation of machine learning models based on modes and functional ANOVA
por: Long, Quan
Publicado: (2024)

Unsupervised Episode Generation for Graph Meta-learning
por: Jung, Jihyeong, et al.
Publicado: (2023)

NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning
por: Ramirez-Sanchez, Edgar, et al.
Publicado: (2025)

Lexicographic optimization-based approaches to learning a representative model for multi-criteria sorting with non-monotonic criteria
por: Zhang, Zhen, et al.
Publicado: (2024)

Data-Centric Interpretability for LLM-based Multi-Agent Reinforcement Learning
por: Yan, John, et al.
Publicado: (2026)

MetaLLMix : An XAI Aided LLM-Meta-learning Based Approach for Hyper-parameters Optimization
por: Bal-Ghaoui, Mohamed, et al.
Publicado: (2025)

Spatiotemporal deep learning models for detection of rapid intensification in cyclones
por: Sutar, Vamshika, et al.
Publicado: (2025)

Operating critical machine learning models in resource constrained regimes
por: Selvan, Raghavendra, et al.
Publicado: (2023)

survex: an R package for explaining machine learning survival models
por: Spytek, Mikołaj, et al.
Publicado: (2023)

From Density Matrices to Phase Transitions in Deep Learning: Spectral Early Warnings and Interpretability
por: Hennick, Max, et al.
Publicado: (2026)

Data efficient surrogate modeling for engineering design: Ensemble-free batch mode deep active learning for regression
por: Kapoor, Sarthak, et al.
Publicado: (2022)

From Explainability to Interpretability: Interpretable Policies in Reinforcement Learning Via Model Explanation
por: Li, Peilang, et al.
Publicado: (2025)

Gradient-free variational learning with conditional mixture networks
por: Heins, Conor, et al.
Publicado: (2024)

Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction
por: Li, Mingchen, et al.
Publicado: (2025)

Guided Safe Shooting: model based reinforcement learning with safety constraints
por: Paolo, Giuseppe, et al.
Publicado: (2022)

Traffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory control
por: Sheng, Zihao, et al.
Publicado: (2024)

Meta-Models: An Architecture for Decoding LLM Behaviors Through Interpreted Embeddings and Natural Language
por: Costarelli, Anthony, et al.
Publicado: (2024)