Key Publications
Coman, A., & Aha, D.W. (2018). AI rebel agents. AI Magazine, 39(3), 16-26.
Hadfield-Menell, D., Russell, S. J., Abbeel, P., & Dragan, A. (2016). Cooperative inverse reinforcement learning. Advances in neural information processing systems, 29, 3909-3917.
More on the importance of alignment between the objectives of AI systems and their users' objectives, see Stuart Russell's talk.
Mirsky, R., & Stone, P. (2021). The seeing-eye robot grand challenge: Rethinking automated care. Proceedings of the Twentieth International Conference on Autonomous Agents and Multiagent Systems (pp. 28-33). Virtual: ACM Press.
Related Work
Aha, D.W., & Coman, A. (2017). The AI rebellion: Changing the narrative. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (pp. 4826-4830). San Francisco, CA: AAAI Press.
Amos-Binks, A., Dannenhauer, D., & Aha, D.W. (2019). Intention dynamics of rebel agent behavior. In Proceedings of the Seventh Annual Conference on Advances in Cognitive Systems. Cambridge, MA: Cognitive Systems Foundation.
Amos-Binks, A., Dannenhauer, D., & Aha, D.W. (2019). Computational models of rebel agent behavior for interactive narrative. In L.H. Gilpin, D. Holmes, & J.C. Macbeth (Eds.) Story-Enabled Intelligence: Papers from the AAAI Spring Symposium (Technical Report SS-19-06). Stanford, CA: AAAI Press.
Apker, T., Johnson, B., & Humphrey, L. (2016). LTL templates for play-calling supervisory control. In Proceedings of the Fifty-Fourth AIAA Science and Technology Forum Exposition. Red Hook, NY: Curran Associates, Inc.
Arnold, T., Kasenberg, D., & Scheutz, M. (2017). Value alignment or misalignment: What will keep systems accountable? In Workshops at the Thirty-First AAAI Conference on Artificial Intelligence.
Banks, J. (2020). Good robots, bad robots: Morally valenced behavior effects on perceived mind, morality, and trust. International Journal of Social Robotics, 13, 2021-2038.
Boggs, J., Dannenhauer, D., Floyd, M.W., & Aha, D.W. (2018). The ideal rebellion: Maximizing task performance in rebel agents. In M. Molineaux, D. Dannenhauer, & M. Roberts (Eds.) Goal Reasoning: Papers from the IJCAI Workshop. Stockholm, Sweden.
Borenstein, J., & Arkin, R. (2016). Robotic nudges: The ethics of engineering a more socially just human being. Science and Engineering Ethics, 22(1), 31–46.
Briggs, G., McConnell, I., & Scheutz, M. (2015). When robots object: Evidence for the utility of verbal, but not necessarily spoken protest. Proceedings of the Seventh International Conference on Social Robotics (pp. 83–92). Berlin: Springer.
Briggs, G., & Scheutz. M. 2015. “Sorry, I Can’t Do That”: Developing Mechanisms to Appropriately Reject Directives in Human-Robot Interactions. In B. Hayes & M. Gombolay (Eds.) Artificial Intelligence for Human-Robot Interaction: Papers from the AAAI Fall Symposium (Technical Report FS-15-01). Palo Alto, CA: AAAI Press.
Briggs, G., Williams, T., Jackson, R. B., & Scheutz, M. (2021). Why and how robots should say ‘No’. International Journal of Social Robotics, 1-17.
Coman, A., & Aha, D.W. (2017). Cognitive support for rebel agents: Social awareness and counternarrative intelligence. In Proceedings of the Fifth Conference on Advances in Cognitive Systems. Troy, NY: Cognitive Systems Foundation.
Dannenhauer, D., Floyd, M., Magazzeni, D., & Aha, D.W. (2018). Explaining rebel behavior in goal reasoning agents. In S. Biundo, P. Langley, D. Magazzeni, & D. Smith (Eds.) Explainable AI Planning: Papers of the ICAPS Workshop. Delft, The Netherlands.
Fisac, J.F., Gates, M.A., Hamrick, J.B., Liu, C., Hadfield-Menell, D., Palaniappan, M., Malik, D., Sastry, S.S., Griffiths, T.L. & Dragan, A.D., (2020). Pragmatic-pedagogic value alignment. In Robotics Research (pp. 49-57). Springer, Cham.
Gregg-Smith, A., & Mayol-Cuevas, W. W. (2015). The design and evaluation of a cooperative handheld robot. In Proceedings of the International Conference on Robotics and Automation. Piscataway, NJ: IEEE Press.
Kress-Gazit, H., Eder, K., Hoffman, G., Admoni, H., Argall, B., Ehlers, R., ... & Sadigh, D. (2021). Formalizing and guaranteeing human-robot interaction. Communications of the ACM, 64(9), 78-84.
Lewis, C., & Norman, D. A. (1995). Designing for error. In Readings in Human–Computer Interaction (pp. 686-697). Morgan Kaufmann.
Meinke, A., Schoen, B., Scheurer, J., Balesni, M., Shah, R., & Hobbhahn, M. (2024). Frontier models are capable of in-context scheming. arXiv preprint arXiv:2412.04984.
Milli, S., Hadfield-Menell, D., Dragan, A., & Russell, S. (2017). Should robots be obedient? arXiv preprint arXiv:1705.09990.
Mirsky, Reuth, and Peter Stone. 2021. Intelligent disobedience and AI rebel agents in assistive robotics. In M. Staffa, M. Khemassi, & F. Cordella (Eds.) Adaptive Social Interaction and MOVement for Assistive and Rehabilitation Robotics: Papers from the IROS Workshop. Singapore: [https://sites.google.com/view/asimov-2021/home].
Mohammad, Z. (2021). A rebellion framework with learning for goal-driven autonomy [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center.
Murphy, R., & Woods, D. D. (2009). Beyond Asimov: The three laws of responsible robotics. IEEE intelligent systems, 24(4), 14-20.
Sarathy, V., Arnold, T., & Scheutz, M. (2019). When exceptions are the norm: Exploring the role of consent in HRI. ACM Transactions on Human-Robot Interaction, 8(3), 1-21.
Ward, F., Toni, F., Belardinelli, F., & Everitt, T. (2024). Honesty is the best policy: Defining and mitigating AI deception. Advances in Neural Information Processing Systems, 36.
Wen, R., Ferraro, F., & Matuszek, C. (2024). GPT-4 as a moral reasoner for robot command rejection. Proceedings of the Twelfth International Conference on Human-Agent Interaction (pp. 54-63). Sansea, UK: ACM Press.