research
∙
02/24/2023
GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations
Counterfactual explanations are a common tool to explain artificial inte...
share
research
∙
10/21/2022
Integrating Policy Summaries with Reward Decomposition for Explaining Reinforcement Learning Agents
Explaining the behavior of reinforcement learning agents operating in se...
research
∙
07/19/2022
Alterfactual Explanations – The Relevance of Irrelevance for Explaining AI Systems
Explanation mechanisms from the field of Counterfactual Thinking are a w...
research
∙
08/19/2021
Dynamic Difficulty Adjustment in Virtual Reality Exergames through Experience-driven Procedural Content Generation
Virtual Reality (VR) games that feature physical activities have been sh...
research
∙
04/15/2021
Do Deep Neural Networks Forget Facial Action Units? – Exploring the Effects of Transfer Learning in Health Related Facial Expression Recognition
In this paper, we present a process to investigate the effects of transf...
research
∙
01/18/2021
Benchmarking Perturbation-based Saliency Maps for Explaining Deep Reinforcement Learning Agents
Recent years saw a plethora of work on explaining complex intelligent ag...
research
∙
12/22/2020
This is not the Texture you are looking for! Introducing Novel Counterfactual Explanations for Non-Experts using Generative Adversarial Learning
With the ongoing rise of machine learning, the need for methods for expl...
research
∙
05/18/2020
