55 citations · 71 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
Real-Time Counterfactual Explanations For Robotic Systems With Multiple Continuous Outputs
Vilde B. Gjærum, Inga Strümke, Anastasios M. Lekkas +1
Although many machine learning methods, especially from the field of deep learning, have been instrumental in addressing challenges within robotic applications, we cannot take full…
Approximating a deep reinforcement learning docking agent using linear model trees
Vilde B. Gjærum, Ella-Lovise H. Rørvik, Anastasios M. Lekkas
Deep reinforcement learning has led to numerous notable results in robotics. However, deep neural networks (DNNs) are unintuitive, which makes it difficult to understand their pred…
Explaining a Deep Reinforcement Learning Docking Agent Using Linear Model Trees with User Adapted Visualization
Vilde B. Gjærum, Inga Strümke, Ole Andreas Alsos +1
Deep neural networks (DNNs) can be useful within the marine robotics field, but their utility value is restricted by their black-box nature. Explainable artificial intelligence met…
Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning
Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas
We investigate the effect of including domain knowledge about a robotic system's causal relations when generating explanations. To this end, we compare two methods from explainable…
Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations
Sindre Benjamin Remman, Anastasios M. Lekkas
This paper deals with robotic lever control using Explainable Deep Reinforcement Learning. First, we train a policy by using the Deep Deterministic Policy Gradient algorithm and th…