|
2024 Conference Publication Towards the New XAI: A Hypothesis-Driven Approach to Decision Support Using EvidenceLe, Thao, Miller, Tim, Sonenberg, Liz and Singh, Ronal (2024). Towards the New XAI: A Hypothesis-Driven Approach to Decision Support Using Evidence. 27th European Conference on Artificial Intelligence, Santiago de Compostela, Spain, 19–24 October 2024. Amsterdam, Netherlands: IOS Press. doi: 10.3233/faia240571 |
|
2024 Conference Publication How to validate XAI in longitudinal studies?Gjoreski, Martin, Laporte, Matias, Langheinrich, Marc and Miller, Tim (2024). How to validate XAI in longitudinal studies?. ACM International Joint Conference on Pervasive and Ubiquitous Computing / ACM International Symposium on Wearable Computers (UbiComp/ISWC), Melbourne, VIC, Australia, 5-9 October 2024. New York, United States: Association for Computing Machinery. doi: 10.1145/3675094.3678997 |
|
2024 Journal Article Using conversant artificial intelligence to improve diagnostic reasoning: ready for prime time?Scott, Ian A., Miller, Tim and Crock, Carmel (2024). Using conversant artificial intelligence to improve diagnostic reasoning: ready for prime time?. Medical Journal of Australia, 221 (5), 240-243. doi: 10.5694/mja2.52401 |
|
2024 Journal Article Capturing the ghost in the machine: a process for development and validation of measures of phenomenal consciousness in deliriumEeles, Eamonn, Tran, David Duc, Ward, Sarah, Teodorczuk, Andrew, Ray, Julian, Miller, Tim and Dissanayaka, Nadeeka N. (2024). Capturing the ghost in the machine: a process for development and validation of measures of phenomenal consciousness in delirium. Age and Ageing, 53 (7) afae144. doi: 10.1093/ageing/afae144 |
|
2024 Book Chapter Demystifying consumer-facing fintech accountability for automated advice toolsPaterson, Jeannie, Miller, Tim and Lyons, Henrietta (2024). Demystifying consumer-facing fintech accountability for automated advice tools. Money, power, and AI: automated banks and automated state. (pp. 29-50) edited by Zofia Bednarz and Monika Zalnieriute. Cambridge, United Kingdom: Cambridge University Press. doi: 10.1017/9781009334297.005 |
|
2024 Book Mastering Reinforcement LearningMiller, Tim (2024). Mastering Reinforcement Learning. Brisbane, Australia: The University of Queensland. doi: 10.14264/4bf1412 |
|
2024 Book Chapter Transforming food production with AICooper, Mark, Hickey, Lee, Jiang, Xianxian, La Fata, Giorgio, Lomas, Harold, Miller, Tim, O’Brien, Susan, Patel, Parth and Tomarchio, Samuel (2024). Transforming food production with AI. Food AI: A game changer for Australia’s food and beverage sector. (pp. 5-13) edited by Janet R. McColl-Kennedy and Damian Hine. Brisbane, QLD, Australia: The University of Queensland, Australia's Food and Beverage Accelerator (FaBA). |
|
2023 Journal Article Directive explanations for actionable explainability in machine learning applicationsSingh, Ronal, Miller, Tim, Lyons, Henrietta, Sonenberg, Liz, Velloso, Eduardo, Vetere, Frank, Howe, Piers and Dourish, Paul (2023). Directive explanations for actionable explainability in machine learning applications. ACM Transactions on Interactive Intelligent Systems, 13 (4) 23, 1-26. doi: 10.1145/3579363 |
|
2023 Conference Publication Algorithmic decisions, desire for control, and the preference for human review over algorithmic reviewLyons, Henrietta, Miller, Tim and Velloso, Eduardo (2023). Algorithmic decisions, desire for control, and the preference for human review over algorithmic review. 2023 ACM Conference on Fairness, Accountability, and Transparency, Chicago, IL, United States, 12–15 June 2023. New York, NY, United States: ACM. doi: 10.1145/3593013.3594041 |
|
2023 Conference Publication Explainable AI is dead, long live explainable AI! : hypothesis-driven decision support using evaluative AIMiller, Tim (2023). Explainable AI is dead, long live explainable AI! : hypothesis-driven decision support using evaluative AI. 2023 ACM Conference on Fairness, Accountability, and Transparency, Chicago, IL, United States, 12–15 June 2023. New York, NY, United States: ACM. doi: 10.1145/3593013.3594001 |
|
2023 Journal Article Model tree methods for explaining deep reinforcement learning agents in real-time robotic applicationsGjaerum, Vilde B., Strumke, Inga, Lover, Jakob, Miller, Timothy and Lekkas, Anastasios M. (2023). Model tree methods for explaining deep reinforcement learning agents in real-time robotic applications. Neurocomputing, 515, 133-144. doi: 10.1016/j.neucom.2022.10.014 |
|
2022 Conference Publication Characterizing text revisions to better support collaborativePing, Tan Ping, Verspoor, Karin and Miller, Timothy (2022). Characterizing text revisions to better support collaborative. 2022 International Conference on Digital Transformation and Intelligence (ICDI), Kuching, Sarawak, Malaysia, 1-2 December 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDI57181.2022.10007395 |
|
2022 Conference Publication What's the appeal? Perceptions of review processes for algorithmic decisionsLyons, Henrietta, Wijenayake, Senuri, Miller, Tim and Velloso, Eduardo (2022). What's the appeal? Perceptions of review processes for algorithmic decisions. CHI Conference on Human Factors in Computing Systems (CHI), New Orleans, LA, United States, 30 April-5 May 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3491102.3517606 |
|
2021 Journal Article Modeling communication of collaborative multiagent system under epistemic planningAlshehri, Abeer, Miller, Tim and Sonenberg, Liz (2021). Modeling communication of collaborative multiagent system under epistemic planning. International Journal of Intelligent Systems, 36 (10), 5959-5980. doi: 10.1002/int.22536 |
|
2020 Journal Article Demand-Driven Transparency for Monitoring Intelligent AgentsVered, Mor, Howe, Piers, Miller, Tim, Sonenberg, Liz and Velloso, Eduardo (2020). Demand-Driven Transparency for Monitoring Intelligent Agents. IEEE Transactions on Human-Machine Systems, 50 (3), 264-275. doi: 10.1109/thms.2020.2988859 |
|
2019 Journal Article XAI—Explainable artificial intelligenceGunning, David, Stefik, Mark, Choi, Jaesik, Miller, Timothy, Stumpf, Simone and Yang, Guang-Zhong (2019). XAI—Explainable artificial intelligence. Science Robotics, 4 (37). doi: 10.1126/scirobotics.aay7120 |
|
2019 Conference Publication Motivational Modelling in Software for Homelessness: Lessons from an Industrial StudyBurrows, Rachel, Lopez-Lorca, Antonio, Sterling, Leon, Miller, Tim, Mendoza, Antonette and Pedell, Sonja (2019). Motivational Modelling in Software for Homelessness: Lessons from an Industrial Study. 2019 IEEE 27th International Requirements Engineering Conference (RE), Jeju, Korea, 23-27 September 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/re.2019.00039 |
|
2018 Journal Article Explaining Explanation, Part 4: A Deep Dive on Deep NetsHoffman, Robert, Miller, Tim, Mueller, Shane T., Klein, Gary and Clancey, William J. (2018). Explaining Explanation, Part 4: A Deep Dive on Deep Nets. Ieee Intelligent Systems, 33 (3), 87-95. doi: 10.1109/MIS.2018.033001421 |
|
2018 Book Chapter Social Planning for Trusted AutonomyMiller, Tim, Pearce, Adrian R. and Sonenberg, Liz (2018). Social Planning for Trusted Autonomy. Foundations of Trusted Autonomy. (pp. 67-86) Cham, Switzerland: Springer. doi: 10.1007/978-3-319-64816-3_4 |
|
2017 Journal Article A framework for automatically ensuring the conformance of agent designsAbushark, Yoosef, Thangarajah, John, Harland, James and Miller, Tim (2017). A framework for automatically ensuring the conformance of agent designs. Journal of Systems and Software, 131, 266-310. doi: 10.1016/j.jss.2017.05.098 |
