Discovering Behavioral Modes in Deep Reinforcement Learning Policies Using Trajectory Clustering in Latent Space

no code implementations • 20 Feb 2024 • Sindre Benjamin Remman, Anastasios M. Lekkas

In this paper, we introduce a new approach for investigating the behavior modes of DRL policies, which involves utilizing dimensionality reduction and trajectory clustering in the latent space of neural networks.

Clustering Dimensionality Reduction +1

Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning

no code implementations • 4 Nov 2021 • Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas

This partial causal ordering defines the causal relations between the features, and we specify this using domain knowledge about the lever control task.

Explainable artificial intelligence Reinforcement Learning (RL)

Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations

no code implementations • 7 Oct 2021 • Sindre Benjamin Remman, Anastasios M. Lekkas

To explain the decisions of the policy we use the SHAP method to create an explanation model based on the episodes done in the real-world environment.

reinforcement-learning Reinforcement Learning (RL)