Jan 29, 2021 · We introduce counterfactual state explanations, a novel example-based approach to counterfactual explanations based on generative deep learning.
We introduce counterfactual state explanations, a novel example-based approach to counterfactual explanations based on generative deep learning.
Counterfactual explanations, which deal with “why not?” scenarios, can provide insightful explanations to an AI agent's behavior [Miller, 2019].
Jan 29, 2021 · A novel but simple method to generate counterfactual explanations for RL agents by formulating the problem as a domain transfer problem ...
Sep 27, 2019 · We introduce a novel method to create counterfactual states from a generative deep learning architecture.
Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning. 5 stars 2 forks Branches Tags Activity.
May 29, 2023 · ABSTRACT. Reinforcement learning (RL) algorithms often use neural networks to represent agent's policy, making them difficult to interpret.
Counterfactual state explanations for reinforcement learning agents via generative deep learning ; Journal: Artificial Intelligence, 2021, p. 103455 ; Publisher: ...
May 30, 2023 · Counterfactual explanations are human-friendly explanations which offer users actionable advice on how to change their features to obtain a desired output from ...
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GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations · Installation · Code Structure & Usage.