Cover Image

Approximating Shapley Explanations in Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Beechey, Daniel, Şimşek, Özgür
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Theoretical Framework for Explaining Reinforcement Learning with Shapley Values
by: Beechey, Daniel, et al.
Published: (2025)

Creating Multi-Level Skill Hierarchies in Reinforcement Learning
by: Evans, Joshua B., et al.
Published: (2023)

Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
by: Panayiotou, Panayiotis, et al.
Published: (2026)

Curricula for Learning Robust Policies with Factored State Representations in Changing Environments
by: Panayiotou, Panayiotis, et al.
Published: (2024)

Suboptimal Shapley Value Explanations
by: Lu, Xiaolei
Published: (2025)

Statistical Inference and Learning for Shapley Additive Explanations (SHAP)
by: Whitehouse, Justin, et al.
Published: (2026)

Accelerating Task Generalisation with Multi-Level Skill Hierarchies
by: Cannon, Thomas P, et al.
Published: (2024)

Hierarchical Orchestra of Policies
by: Cannon, Thomas P, et al.
Published: (2024)

SIM-Shapley: A Stable and Computationally Efficient Approach to Shapley Value Approximation
by: Fan, Wangxuan, et al.
Published: (2025)

Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
by: Parafita, Álvaro, et al.
Published: (2025)

Learning The Minimum Action Distance
by: Steccanella, Lorenzo, et al.
Published: (2025)

Provably Adaptive Linear Approximation for the Shapley Value and Beyond
by: Li, Weida, et al.
Published: (2026)

Unifying Prediction and Explanation in Time-Series Transformers via Shapley-based Pretraining
by: Cheng, Qisen, et al.
Published: (2025)

Proxy-Based Approximation of Shapley and Banzhaf Interactions
by: Thies, Santo M. A. R., et al.
Published: (2026)

Shapley Values: Paired-Sampling Approximations
by: Mayer, Michael, et al.
Published: (2025)

GNNShap: Scalable and Accurate GNN Explanation using Shapley Values
by: Akkas, Selahattin, et al.
Published: (2024)

Joint Distribution-Informed Shapley Values for Sparse Counterfactual Explanations
by: You, Lei, et al.
Published: (2024)

Error Analysis of Shapley Value-Based Model Explanations: An Informative Perspective
by: Zhao, Ningsheng, et al.
Published: (2024)

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies
by: Simsir, Hikmet, et al.
Published: (2026)

Approximating the Shapley Value without Marginal Contributions
by: Kolpaczki, Patrick, et al.
Published: (2023)

CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
by: Panayiotou, Panayiotis, et al.
Published: (2025)

Action Shapley: A Training Data Selection Metric for World Model in Reinforcement Learning
by: Ghosh, Rajat, et al.
Published: (2026)

Shapley Value Approximation Based on k-Additive Games
by: Pelegrina, Guilherme Dean, et al.
Published: (2025)

DistShap: Scalable GNN Explanations with Distributed Shapley Values
by: Akkas, Selahattin, et al.
Published: (2025)

Approximate Equivariance in Reinforcement Learning
by: Park, Jung Yeon, et al.
Published: (2024)

Shapley Marginal Surplus for Strong Models
by: de Marchi, Daniel, et al.
Published: (2024)

Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
by: Poinsot, Audrey, et al.
Published: (2025)

FW-Shapley: Real-time Estimation of Weighted Shapley Values
by: Panda, Pranoy, et al.
Published: (2025)

Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning
by: Zha, Yantian, et al.
Published: (2021)

A Tutorial: An Intuitive Explanation of Offline Reinforcement Learning Theory
by: Che, Fengdi
Published: (2025)

Counterfactual Explanations for Continuous Action Reinforcement Learning
by: Dong, Shuyang, et al.
Published: (2025)

Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning
by: Mahadevan, Vagul, et al.
Published: (2026)

DemoShapley: Valuation of Demonstrations for In-Context Learning
by: Xie, Shan, et al.
Published: (2024)

shapiq: Shapley Interactions for Machine Learning
by: Muschalik, Maximilian, et al.
Published: (2024)

Fairness-Aware Federated Learning with Trajectory Shapley Value
by: Kuznetsov, Daniel, et al.
Published: (2026)

Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity
by: Levy, Jordan, et al.
Published: (2026)

Replicable Reinforcement Learning with Linear Function Approximation
by: Eaton, Eric, et al.
Published: (2025)

Nonstationary Reinforcement Learning with Linear Function Approximation
by: Zhou, Huozhi, et al.
Published: (2020)

The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
by: Liu, Shuze Daniel, et al.
Published: (2024)

Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Framework
by: Russo, Fabrizio, et al.
Published: (2023)