Explainable Agency for Intelligent Autonomous Systems

Human Problem Solving.

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Building Watson: An Overview of the DeepQA Project

Ferrucci, D. A., Brown, E. W., Chu‐Carroll, J., Fan, J., Gondek, D. C., Kalyanpur, A. A., Lally, A., Murdock, J. W., Nyberg, E., Prager, J. M., et al. (2010) · AI Magazine · doi:10.1609/aimag.v31i3.2303 · Cited by 1,523

Explanation in Second Generation Expert Systems

Swartout, W. R., & Moore, J. D. (1993) · Second Generation Expert Systems · doi:10.1007/978-3-642-77927-5_24 · Cited by 160

Agents that Learn to Explain Themselves

Johnson, W. L. (1994) · Cited by 93

Plan Explainability and Predictability for Cobots.Preprint

Zhang, Y., Zhuo, H. H., & Subbarao Kambhampati, B. (2015) · arXiv (Cornell University) · Cited by 5

Self-Explaining Abilities of an Intelligent Agent for Transparency in a Collaborative Driving Context

Kridalukmana, R., Lu, H., & Naderpour, M. (2022) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2022.3202900 · Cited by 6

Investigating Car Drivers’ Information Demand after Safety and Security Critical Incidents

Gröber, L., Fassl, M., Gupta, A., & Krombholz, K. (2021) · International Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3446862 · Cited by 5

An Argumentation-Based Approach for Explaining Goals Selection in Intelligent Agents

Morveli-Espinoza, M., Tacla, C. A., & Jasinski, H. M. R. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-61380-8_4 · Cited by 5

Enhancing Trust in Autonomous Agents: An Architecture for Accountability and Explainability Through Blockchain and Large Language ModelsPreprint

Fernández-Becerra, L., González-Santamarta, M. Á., Guerrero‐Higueras, Á. M., Rodríguez-Lera, F. J., & Olivera, V. M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4773675 · Cited by 9

Developing Autopilot Agent Transparency for Collaborative Driving

Kridalukmana, R., Eridani, D., Septiana, R., Rochim, A. F., & Setyobudhi, C. T. (2022) · International Joint Conference on Computer Science and Software Engineering · doi:10.1109/jcsse54890.2022.9836249 · Cited by 4

Explainable Data Fusion on Edge: Challenges and Opportunities

Sinha, S., & Vashisht, P. (2022) · Studies in computational intelligence · doi:10.1007/978-3-031-18292-1_8 · Cited by 4

User Interfaces and Scheduling and Planning: Workshop Summary and Proposed Challenges.

Freedman, R. G., Chakraborti, T., Talamadupula, K., Magazzeni, D., & Frank, J. (2018) · Research Portal (King's College London) · Cited by 4

Extracting Reasons for Moral Judgments Under Various Ethical Principles

Lindner, F., & Möllney, K. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-30179-8_18 · Cited by 5

Axiom Learning and Belief Tracing for Transparent Decision Making in RoboticsPreprint

Mota, T., & Sridharan, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.10645 · Cited by 4

Road scene map for autonomous driving and modeling method

Lei, J., You, X., Tian, J., Yang, J., Gao, K., & Liu, W. (2025) · International Journal of Digital Earth · doi:10.1080/17538947.2025.2505623 · Cited by 3

Agent Allocation of Moral Decisions in Human-Agent Teams: Raise Human Involvement and Explain Potential Consequences

Verhagen, R., Neerincx, M. A., & Tielman, M. L. (2025) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3715275.3732157 · Cited by 3

Generating trustworthy and context-aware explanations for autonomous robots using an LLM agent-based RAG architecture

Fernández-Becerra, L., Guerrero-Higueras, Á., Rodríguez-Lera, F. J., & Olivera, V. M. (2026) · Expert systems with applications · doi:10.1016/j.eswa.2026.132631 · Cited by 3

Optimizing pathfinding for goal legibility and recognition in cooperative partially observable environments

Bernardini, S., Fagnani, F., Neacsu, A., & Franco, S. (2024) · Artificial Intelligence · doi:10.1016/j.artint.2024.104148 · Cited by 3

Explainable Agency by Revealing Suboptimality in Child-Robot Learning Scenarios

Tulli, S., Couto, M., Vasco, M., Yadollahi, E., Melo, F. S., & Paiva, A. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-62056-1_3 · Cited by 3

Explainable Goal Recognition: A Framework Based on Weight of Evidence

Alshehri, A. S., Miller, T., & Vered, M. (2023) · Proceedings of the International Conference on Automated Planning and Scheduling · doi:10.1609/icaps.v33i1.27173 · Cited by 3

Dungeon Crawl Stone Soup as an Evaluation Domain for Artificial IntelligencePreprint

Dannenhauer, D., Floyd, M. W., Decker, J. W., & Aha, D. W. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.01769 · Cited by 3

Progressive Explanation Generation for Human-robot TeamingPreprint

Zhang, Y., & Zakershahrak, M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.00604 · Cited by 3

Towards Explainable and Trustworthy Autonomous Physical Systems

Omeiza, D., Anjomshoae, S., Kollnig, K., Camburu, O.-M., Främling, K., & Kunze, L. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411763.3441338 · Cited by 2

Fully Embedded Learning in BDI Agents Programmed in ASTRA

Beaumont, K., & Collier, R. (2026) · Springer eBooks · doi:10.1007/978-3-032-01082-7_10 · Cited by 2

Preference Elicitation and Explanation in Iterative Planning

Sanneman, L. (2019) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2019/917 · Cited by 2

Toward a Cognitive Control Framework for Explainable Robotics

Caccavale, R., & Finzi, A. (2021) · Springer proceedings in advanced robotics · doi:10.1007/978-3-030-71356-0_4 · Cited by 2

Towards a Holistic Framework for Explainable Robot Navigation

Halilovic, A., & Krivić, S. (2024) · Springer proceedings in advanced robotics · doi:10.1007/978-3-031-55000-3_15 · Cited by 2

Chess and explainable AI

Björnsson, Y. (2024) · ICGA Journal · doi:10.3233/icg-240256 · Cited by 2

Back to the Future of Integrated Robot Systems

Sridharan, M. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v39i27.35085 · Cited by 2

Explaining Intelligent Agent’s Future Motion on Basis of Vocabulary Learning With Human Goal Inference

Fukuchi, Y., Osawa, M., Yamakawa, H., & Imai, M. (2022) · IEEE Access · doi:10.1109/access.2022.3176104 · Cited by 2

BEE: Belief-Value-Aligned, Explainable, and Extensible Cognitive Framework for Conversational Agents

Yang, C., Groß, M. H., & Wampfler, R. (2025) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3717511.3747067 · Cited by 1

Engineering Inter-agent Explainability in BDI Agents

Beaumont, K., Yan, E., Burattini, S., & Collier, R. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-01399-6_9 · Cited by 1

The Role of Accounts and Apologies in Mitigating Blame toward Human and Machine Agents

Stowers, K. L. (2017) · Journal of International Crisis and Risk Communication Research · Cited by 1

A Network Flow Interpretation of Robust Goal Legibility in Path Finding

Bernardini, S., Fagnani, F., Franco, S., & Neacsu, A. (2022) · Proceedings of the International Conference on Automated Planning and Scheduling · doi:10.1609/icaps.v32i1.19856 · Cited by 1

Grounding Robot Navigation in Self-Defense Law

Zhu, J., Shrivastava, A., & Johnson, A. M. (2023) · IEEE RO-MAN · doi:10.1109/ro-man57019.2023.10309428 · Cited by 1

Development and Evaluation of Exploratory Experiences to Facilitate Reasoning About Robotic Systems

Balali, S., Hudspeth, M., Afflerbach, I., Helgesen, H., McCurry, J., Al-Afia, W. A., Bruslind, K., Hays, K., Sowell, R. T., West, R. G., et al. (2023) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros55552.2023.10342409 · Cited by 1

An Education Model of Reasonable and Good-Faith Effort for Autonomous Systems

Grimm, C. M., Smart, W. D., & Hartzog, W. (2018) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3278721.3278732 · Cited by 1

Explanation of Reinforcement Learning Model in Dynamic Multi-Agent SystemPreprint

Wang, X., Li, H., Zhang, H., Lewis, M. A., & Sycara, K. P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.01508 · Cited by 6

An Argumentation-based Approach for Explaining Goal Selection in Intelligent AgentsPreprint

Morveli-Espinoza, M., Tacla, C. A., & Jasinski, H. M. R. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.06131 · Cited by 1

Human-centered Interactions with Text Classifiers : Fusing Concept-based Knowledge with Local Surrogate Explanation Models

Kiefer, S. (2023) · doi:10.20378/irb-89771 · Cited by 1

Explaining Possible Futures for Robust Autonomous Decision-Making.

Gilpin, L. H. (2019) · National Conference on Artificial Intelligence

A Unifying Bayesian Formulation of Measures of Interpretability in Human-AIPreprint

Sreedharan, S., Kulkarni, A., Smith, D. E., & Subbarao Kambhampati, B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.10743

An Approach to Modeling Simulated Military Human-agent Teaming

Hidalgo, M. (2020) · Journal of International Crisis and Risk Communication Research

Towards Explainable Practical Agency

Ehab, N., & Ismail, H. O. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-82017-6_16

Mensch-Maschine-Zusammenarbeit bei der Entscheidungsfindung

Hatz, A., Jaklič, J., & Morelli, F. (2022) · Anwendungen und Konzepte der Wirtschaftsinformatik · doi:10.26034/lu.akwi.2022.3338

Exploring Trust and Explainability of Unmanned Systems

Field, J. R. (2023) · MTS/IEEE OCEANS Conference (OCEANS) · doi:10.1109/oceanslimerick52467.2023.10244349

Erklärbare Künstliche Intelligenz im Kontext von Bildung und Lernen

Weitz, K. (2023) · Springer eBooks · doi:10.1007/978-3-658-40079-8_20

Freedom Without Conscience: Computational Compatibilism and Moral Attribution in Artificial Intelligence Systems

Morandín-Ahuerma, F. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2565393 · Cited by 1

On the Need of a Decolonized AI Ethics and Governance Framework for Human-GenAI Cooperation in the Art Sector: A Roadmap

Pansoni, S., Beck, E., & Tiribelli, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-01399-6_11

Towards Explainable BDI Agents for End Users

Mauri, M., & Minor, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-18011-7_13

Collaboration humain-machine à l’aide de motifs dialogiques pour la réalisation d’une tâche complexe : application à la recherche d’information

Louvet, J.-B. (2019) · theses.fr (ABES) · doi:10.70675/4dc73ff6z89d7z45f6za5bez8b3748278491

Toward interpretable machine learning, with applications to large-scale industrial systems data

Mita, G. (2021) · theses.fr (ABES) · doi:10.70675/acfd6da1z8046z49d6z8c4ez2da37571763c

A Neural-Symbolic learning framework to produce interpretable predictions for image classification

Bennetot, A. (2022) · theses.fr (ABES) · doi:10.70675/2b59f598z2028z49afz8a20z29b21f19f394

Collaborate and explain on-the-fly: knowledge-based reasoning and learning in ad hoc teamwork

Dodampegama, H., & Sridharan, M. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2026.1765191

Explainable AI for HCI: a systematic review of a decade of studies on XAI tools

Alaqsam, A., & Sas, C. (2026) · Interacting with Computers · doi:10.1093/iwc/iwag022

Evaluating Actionability in Explainable AI

Mansi, G., Kim, J., & Riedl, M. O. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30849-8_5 · Cited by 1

Explainable Action Chains in Agentic AI: Enhancing Transparency and Trust

Selimi, A., Ali, İ., & Cafer, C. (2026) · Journal of AI · doi:10.61969/jai.1955038

Agent Toolkits: Explainable Agency in ASTRA

Beaumont, K., Yan, E., Burattini, S., & Collier, R. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-22817-8_5

Explanation Needs Emerge Before Explicit Requests in Human-Robot Interaction

Kontogiorgos, D., Gustafson, J., & Shah, J. (2026) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3776574.3831198

Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences

Miller, T., Howe, P., & Sonenberg, L. (2017) · arXiv · doi:10.48550/arxiv.1712.00547 · Cited by 218

Explainable Goal-Driven Agents and Robots -- A Comprehensive Review and New FrameworkPreprint

Fatai, S., Loo, C. K., Kerzel, M., & Wermter, S. (2020) · arXiv (Cornell University) · Cited by 11

Explainable Agency in Artificial Intelligence

Tulli, S., & Aha, D. W. (2023) · CRC Press eBooks · doi:10.1201/9781003355281 · Cited by 1

Explainable Agents for Less Bias in Human-Agent Decision Making

Malhi, A. K., Knapič, S., & Främling, K. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-51924-7_8 · Cited by 37

Explainable goal-driven agents and robots-a comprehensive review

Sado, F., Loo, C. K., Liew, W. S., Kerzel, M., & Wermter, S. (2023) · ACM Computing Surveys · doi:10.1145/3564240 · Cited by 79

A Surrogate Model Framework for Explainable Autonomous BehaviourPreprint

Gavriilidis, K., Munafò, A., Pang, W., & Hastie, H. F. (2023) · arXiv.org · doi:10.48550/arxiv.2305.19724 · Cited by 16