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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 |
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2024 Conference Publication Preface of the Proceedings of the Workshop on Multimodal, Affective and Interactive eXplainable Artificial Intelligence (MAI-XAI), collocated with the European Conference on Artificial Intelligence (ECAI), 2024Alonso-Moral, Jose M., Anthis, Zach, Berlanga, Rafael, Catalá, Alejandro, Cimiano, Philipp, Flach, Peter, Hüllermeier, Eyke, Miller, Tim, Mitruț, Oana, Moise, Gabriela, Moldoveanu, Alin, Moldoveanu, Florica, Sokol, Kacper and Soroa, Aitor (2024). Preface of the Proceedings of the Workshop on Multimodal, Affective and Interactive eXplainable Artificial Intelligence (MAI-XAI), collocated with the European Conference on Artificial Intelligence (ECAI), 2024. 27th European Conference on Artificial Intelligence (ECAI) 2024, Santiago de Compostela, Spain, 19–24 October 2024. Aachen, Germany: Rheinisch-Westfaelische Technische Hochschule Aachen. |
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2024 Book Mastering Reinforcement LearningMiller, Tim (2024). Mastering Reinforcement Learning. Brisbane, QLD Australia: The University of Queensland. doi: 10.14264/4bf1412 |
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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). |
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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 |
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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 |
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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 |
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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 |
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2022 Journal Article Technology for societal change: evaluating a mobile app addressing the emotional needs of people experiencing homelessnessBurrows, Rachel, Mendoza, Antonette, Pedell, Sonja, Sterling, Leon, Miller, Tim and Lopez-Lorca, Alexi (2022). Technology for societal change: evaluating a mobile app addressing the emotional needs of people experiencing homelessness. Health Informatics Journal, 28 (4) 14604582221146720. doi: 10.1177/14604582221146720 |
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2022 Journal Article Efficient multi-agent epistemic planning: teaching planners about nested beliefMuise, Christian, Belle, Vaishak, Felli, Paolo, McIlraith, Sheila, Miller, Tim, Pearce, Adrian R. and Sonenberg, Liz (2022). Efficient multi-agent epistemic planning: teaching planners about nested belief. Artificial Intelligence, 302 103605, 1-36. doi: 10.1016/j.artint.2021.103605 |
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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 |
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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 |
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2022 Journal Article Planning with Perspectives - Decomposing Epistemic Planning using Functional STRIPSHu, Guang, Miller, Tim and Lipovetzky, Nir (2022). Planning with Perspectives - Decomposing Epistemic Planning using Functional STRIPS. Journal of Artificial Intelligence Research, 75, 489-539. |
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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 |
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2021 Conference Publication Invertible concept-based explanations for CNN models with non-negative concept activation vectorsZhang, Ruihan, Madumal, Prashan, Miller, Tim, Ehinger, Krista A. and Rubinstein, Benjamin I. P. (2021). Invertible concept-based explanations for CNN models with non-negative concept activation vectors. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence, Virtual, 2-9 February 2021. Palo Alto, CA United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v35i13.17389 |
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2021 Journal Article Contrastive explanation: a structural-model approachMiller, Tim (2021). Contrastive explanation: a structural-model approach. The Knowledge Engineering Review, 36 e14, 1-24. doi: 10.1017/s0269888921000102 |
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2020 Journal Article Combining gaze and AI planning for online human intention recognitionSingh, Ronal, Miller, Tim, Newn, Joshua, Velloso, Eduardo, Vetere, Frank and Sonenberg, Liz (2020). Combining gaze and AI planning for online human intention recognition. Artificial Intelligence, 284 103275, 1-16. doi: 10.1016/j.artint.2020.103275 |
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2020 Journal Article Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping reviewPayrovnaziri, Seyedeh Neelufar, Chen, Zhaoyi, Rengifo-Moreno, Pablo, Miller, Tim, Bian, Jiang, Chen, Jonathan H., Liu, Xiuwen and He, Zhe (2020). Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review. Journal of the American Medical Informatics Association, 27 (7), 1173-1185. doi: 10.1093/jamia/ocaa053 |
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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 |
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2020 Conference Publication A Closer Look at Generalisation in RAVENSpratley, Steven, Ehinger, Krista and Miller, Tim (2020). A Closer Look at Generalisation in RAVEN. 16th European Conference on Computer Vision-ECCV-Biennial, Online, 23-28 August 2020. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-58583-9_36 |
