Riedl, Mark O.

Expanding Explainability: Towards Social Transparency in AI systems

Ehsan, U., Liao, Q. V., Muller, M., Riedl, M. O., & Weisz, J. D. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 538

Narrative Planning: Balancing Plot and Character

Riedl, M. O., & Young, R. M. (2010) · Journal of Artificial Intelligence Research

Artificial Intelligence in GamesAI-based Problem Solving and Planning

Cited by 522

Interactive Narrative: An Intelligent Systems Approach

Riedl, M. O., & Bulitko, V. (2013) · AI Magazine

Artificial Intelligence in GamesNarrative Theory and Analysis

Cited by 299

Human-Centered Explainable AI: Towards a Reflective Sociotechnical Approach

Ehsan, U., & Riedl, M. O. (2020) · Lecture Notes in Computer Science

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 274

Automated rationale generation: a technique for explainable AI and its effects on human perceptions

Ehsan, U., Tambwekar, P., Chan, L., Harrison, B., & Riedl, M. O. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)AI-based Problem Solving and Planning

Cited by 210

The Who in XAI: How AI Background Shapes Perceptions of AI Explanations

Ehsan, U., Passi, S., Liao, Q. V., Chan, L., Lee, I.-H., Muller, M., & Riedl, M. O. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 123

Human-Centered Explainable AI (HCXAI): Beyond Opening the Black-Box of AI

Ehsan, U., Wintersberger, P., Liao, Q. V., Watkins, E. A., Manger, C., Daumé III, H., Riener, A., & Riedl, M. O. (2022) · CHI Conference on Human Factors in Computing Systems Extended Abstracts

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 117

Explainability Pitfalls: Beyond Dark Patterns in Explainable AI

Ehsan, U., & Riedl, M. O. (2021) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 99

Explainability pitfalls: beyond dark patterns in explainable AI

Ehsan, U., & Riedl, M. O. (2024) · Patterns

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 72

Co-Creative Level Design via Machine Learning

Guzdial, M., Liao, N., & Riedl, M. (2018) · arXiv

Artificial Intelligence in GamesComputer Graphics and Visualization Techniques

Cited by 56

Integrating plan-based behavior generation with game environments

Young, R. M., & Riedl, M. O. (2005) · Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology

Artificial Intelligence in GamesAI-based Problem Solving and Planning

Cited by 21

Plug-and-Blend: A Framework for Plug-and-Play Controllable Story Generation with Sketches

Lin, Z., & Riedl, M. O. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment

Artificial Intelligence in GamesTopic Modeling

Cited by 16

Neuro-Symbolic World Models for Adapting to Open World Novelty

Balloch, J., Lin, Z., Wright, R., Peng, X., Hussain, M., Srinivas, A., Kim, J., & Riedl, M. O. (2023) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 8

Legally-Informed Explainable AI

Mansi, G., Karusala, N., & Riedl, M. (2025) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 4

Dialogue Shaping: Empowering Agents through NPC Interaction

Zhou, W., Peng, X., & Riedl, M. (2023) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 4

Novelty Detection in Reinforcement Learning with World Models

Zollicoffer, G., Eaton, K., Balloch, J., Kim, J., Zhou, W., Wright, R., & Riedl, M. O. (2023) · arXiv

Reinforcement Learning in RoboticsAnomaly Detection Techniques and Applications

Cited by 2

The Role of Exploration for Task Transfer in Reinforcement Learning

Balloch, J. C., Kim, J., Inman, A. J. L., & Riedl, M. O. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 1