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

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cs.LG2024

Deep Reinforcement Learning Behavioral Mode Switching Using Optimal Control Based on a Latent Space Objective

Sindre Benjamin Remman, Bjørn Andreas Kristiansen, Anastasios M. Lekkas

In this work, we use optimal control to change the behavior of a deep reinforcement learning policy by optimizing directly in the policy's latent space. We hypothesize that distinc…

cs.LG2024★ 1 cited

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

Sindre Benjamin Remman, Anastasios M. Lekkas

Understanding the behavior of deep reinforcement learning (DRL) agents is crucial for improving their performance and reliability. However, the complexity of their policies often m…