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Anastasios M. Lekkas

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.RO1
ORCID 0000-0001-6885-6372

identity via Semantic Scholar / OpenAlex

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

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.RO2025

Realistic Counterfactual Explanations for Machine Learning-Controlled Mobile Robots using 2D LiDAR

Sindre Benjamin Remman, Anastasios M. Lekkas

This paper presents a novel method for generating realistic counterfactual explanations (CFEs) in machine learning (ML)-based control for mobile robots using 2D LiDAR. ML models, e…

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…

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