On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data

On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data

In this paper, we address the issues of the explainability of reinforcement learning-based machine learning agents trained with Proximal Policy Optimization (PPO) that utilizes visual sensor data. We propose an algorithm that allows an effective and intuitive approximation of the PPO-trained neural...

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Bibliographic Details
Main Authors: Tomasz Hachaj, Marcin Piekarczyk
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Applied Sciences
Subjects:
reinforcement learning
proximal policy optimization
explainability
GradCAM
decision tree
visual sensor
Online Access:https://www.mdpi.com/2076-3417/15/2/538
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