Using Perceptual and Cognitive Explanations for Enhanced Human-Agent Team Performance

By Mark Antonius Neerincx, Jasper van der Waa, Frank Kaptein, J. Diggelen. 2018

86 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Social Psychology, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Christian Walter Peter Omlin
2. Waddah Saeed
3. Martin Pereira-Fariña
4. Ilia Stepin
5. Alejandro Catalá
6. J. Alonso
7. Henrik Jacobsson
8. J. Urgen Schmidhuber

Citations in the corpus

• A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021, background): “However, whereas certain publications do not provide any specific evaluation method, some do stress that human evaluation should be encouraged to estimate the quality and effectiveness of the generated counterfactuals [46], [150], [153].”
• Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities (2021, background): “Here, the focus is on what content end users will receive and how to present that content [117].”
• Explainable Agents and Robots: Results from a Systematic Literature Review (2019, background): “Aiming to integrate the user into the loop, and to address issues related to explanation communications, the authors in [74] distinguish three explanation phases:”