Publications

2025

• Thabtah, F., & Peebles, D. (2025). Cognitive feature evaluation for disease progression in dementia and its precursors using feature selection. Health and Technology.

2024

• Phillips, C., Peebles, D., & Wilmott, D. (2024). Emotional versus neutral trial language on mock jury recall, moral disengagement and verdict harshness ratings within an acquaintance rape trial. Polish Psychological Bulletin.


• Peebles, D. (2024). Predicting learning and retention in a complex task. Proceedings of the 22nd Annual Conference on Cognitive Modelling. July 19--22, Tilburg, The Netherlands.


• Peebles, D., & Street, C. N. H. (2024). Combining individuating and context-general cues in lie detection. Proceedings of the 46th Annual Meeting of the Cognitive Science Society. July 24--27, Rotterdam, The Netherlands.

2023

• Thabtah, F., & Peebles, D. (2023). Assessment for Alzheimer's disease advancement using classification models with rules. Applied Sciences. 13(22):12152.


• Teal, J., Buontempo, M., Kusev, P., Peebles, D., & Ngo, B. (2023). Democratising professional bra-fitting using Artificial Intelligence. Report for the Future Fashion Factory Digitally Enabled Design & Manufacture of Designer Products for Circular Economies research programme.


• Jazzaa, H., McCluskey, T., & Peebles, D. (2023). Improving task planning knowledge robustness for autonomous robots. Robotics and Autonomous Systems.

2022

• Thabtah, F., Ong, S., & Peebles, D. (2022). Examining cognitive factors for Alzheimer's disease progression using computational intelligence. Healthcare. 10(10), p. 2045.


• Thabtah, F., Ong, S., & Peebles, D. (2022). Detection of dementia progression from functional activities data using machine learning techniques. Intelligent Decision Technologies, 16(3), pp. 615--630.


• Jazzaa, H., McCluskey, T., & Peebles, D. (2022). Improving task planning knowledge robustness for autonomous robots. The 10th ICAPS Workshop on Planning and Robotics, PlanRob 2022.


• Thabtah, F., Spencer, R., & Peebles, D. (2022). Common dementia screening procedures: DSM-5 fulfilment and mapping to cognitive domains. International Journal of Behavioural and Healthcare Research (IJBHR), 8, 1/2, pp. 104-120.


• Peebles, D. (2022). Testing the Predictive Performance Equation: An Experimental Study. Report for Defence Science and Technology Laboratory, Future Workforce and Human Performance (FWaHP) research programme, Ministry of Defence.

2021

• Mathew, R. K., The Immersive Healthcare Collaboration, Mushtaq, F. (2021). Three principles for the progress of immersive technologies in healthcare training & education. BMJ Simulation & Technology Enhanced Learning.


• The Immersive Healthcare Collaboration. (2021). Immersive Technology in Healthcare Training & Education: Three Principles for Progress. Publisher: Centre for Immersive Technologies, Leeds, UK.

2020

• Peebles, D. (2020). Personalised Training Using the Predictive Performance Equation. Report for Defence Science and Technology Laboratory, Future Workforce and Human Performance (FWaHP) research programme, Ministry of Defence.


• Jazzaa, H., McCluskey, T., & Peebles, D. (2020). Reasoning by anomaly detection to improve planning robustness for autonomous robots in changing environments. The 35th Workshop of the UK Planning & Scheduling Special Interest Group, PlanSIG 2020.


• Thabtah, F., Peebles, D., Retzler, J., & Hathurusingha, C. (2020). Dementia medical screening using mobile applications: A systematic review with a new mapping model. Journal of Biomedical Informatics.


• Thabtah, F., Peebles, D., Retzler, J., & Hathurusingha, C. (2020). A review of dementia screening tools based on mobile application. Health and Technology.


• Abdelhamid, N., Padmavathy, A., Peebles, D., Thabtah, F., & Goulder-Horobin, D. (2020). Data imbalance in autism pre-diagnosis classification systems: An experimental study. Journal of Information & Knowledge Management, 19(1).


• Thabtah, F., Mampusti, E., Peebles, D., Herradura, R., & Varghese, J. (2020). A mobile-based screening system for data analyses of early dementia traits detection. Journal of Medical Systems, 44(1), 24.

2019

• Thabtah, F. & Peebles, D. (2019b). Early autism screening: A comprehensive review. International Journal of Environmental Research and Public Health.


• Thabtah, F., Abdelhamid, N., & Peebles, D. (2019). A machine learning autism classification based on logistic regression analysis. Health Information Science and Systems.


• Peebles, D. (2019). Modelling mental imagery in the ACT-R cognitive architecture. In A. Goel, C. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal, Canada.


• Peebles, D. (2019). Modelling alternative strategies for mental rotation. In Proceedings of the 17th International Conference on Cognitive Modelling. Montreal, Canada.


• Thabtah, F. & Peebles, D. (2019a). A new machine learning model based on induction rules for autism detection. Health Informatics Journal.

2018

• Ali, N. & Peebles, D. (2018). The effect of graphical format and instruction on the interpretation of three-variable bar and line graphs. In P. Chapman, G. Stapleton, A. Moktefi, S. Perez-Kriz, and F. Bellucci (Eds.), Proceedings of the 10th International Conference on the Theory and Application of Diagrams, June 18th--22nd, 2018.


• Pulijala, Y., Ma, M., Pears, M., Peebles, D., Ayoub, A. (2018). An innovative virtual reality training tool for orthognathic surgery. International Journal of Oral & Maxillofacial Surgery

2017

• Pulijala, Y., Ma, M., Pears, M., Peebles, D., Ayoub, A. (2017). Effectiveness of immersive virtual reality in surgical training—A randomized control trial. Journal of Oral and Maxillofacial Surgery


• Peebles, D., & Cheng, P. C.-H. (2017). Multiple Representations in Cognitive Architectures. AAAI Fall Symposium 2017: "A Standard Model of the Mind", Washington, USA, November 9-11.


• Cooper, R. P., & Peebles, D. (2017). On the Relation Between Marr's Levels: A Response to Blokpoel. Topics in Cognitive Science. 1-5.


• Peebles, D. & McCluskey, T. L. (2017). Autonomous Agents. Report for Defence Science and Technology Laboratory, Defence and Security Analysis Division, Ministry of Defence.


• Ward, P., Hoffman, R. R., Conway, G. E., Schraagen, J. M., Peebles, D., Hutton, R. J. B., and Petushek, E. J. (2017). Editorial: Macrocognition: The Science and Engineering of Sociotechnical Work Systems.

2016

• Peebles, D. (2016). Two methods for search and optimising cognitive model parameters. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling (pp. 234-235). University Park, PA: Penn State.

2015

• Peebles, D., & Ali, N. (2015). Expert interpretation of bar and line graphs: The role of graphicacy in reducing the effect of graph format. Frontiers in Psychology, 6:1673. DOI: 10.3389/fpsyg.2015.01673


• Peebles, D., & Cooper, R. P. (2015). Thirty years after Marr's Vision: Levels of analysis in cognitive science. Topics in Cognitive Science, 7, 187-190.


• Cooper, R. P., & Peebles, D. (2015). Beyond single-level accounts: The role of cognitive architectures in cognitive scientific explanation. Topics in Cognitive Science, 7, 243-258.

2014

• Peebles, D. & Ramduny-Ellis, D. (2014). Computational modelling of human performance with unmanned autonomous systems using the ACT-R cognitive architecture. Report for Dstl funded 'Autonomous Systems Underpinning Research' (ASUR) programme project.


• Peebles, D. & Jones, C. (2014). A model of object location memory. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 2747-2752). Austin, TX: Cognitive Science Society.

2013

• Ali, N. & Peebles, D. (2013). Reactivity effects of concurrent verbalisation during a graph comprehension task. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 1720-1725). Austin, TX: Cognitive Science Society.


• Peebles, D. (2013). Strategy and pattern recognition in expert comprehension of 2 x 2 interaction graphs. Cognitive Systems Research, 24, 43-51.


• Bonner, J. & Peebles, D. (2013). Rhetorical considerations for innovative approaches to performance and audience engagement. Proceedings of the 2013 Inputs-Outputs Conference: An Interdisciplinary Conference on Engagement in HCI and Performance, Brighton, UK. Association for Computing Machinery.


• Ali, N. & Peebles, D. (2013). The effect of Gestalt laws of perceptual organisation on the comprehension of three-variable bar and line graphs. Human Factors, 55 (1), 183-203.


• van Rijn, H., Russwinkel, N., & Peebles, D. (2013). Editorial. Cognitive Systems Research. 24. 1.

2012

• Eliasmith, C., Griffiths, T., Hardcastle, V. G., Love, B. C., Bechtel, W., Cooper, R. C., & Peebles, D. (2012). Thirty years of Marr's Vision: Levels of analysis in cognitive science. In N. Miyake, D. Peebles, & R. P. Cooper, Proceedings of the 34th Annual Conference of the Cognitive Science Society, Sapporo, Japan.


• Peebles, D. (2012). A cognitive architecture-based model of graph comprehension. In N. Russwinkel, U. Drewitz, J. Dzaack, & H. van Rijn, Proceedings of the 11th International Conference on Cognitive Modeling, Berlin, Germany.


• Bonner, J., Ramduny-Ellis, D., & Peebles, D. (2012). Making audience experiences more meaningful and emotionally engaging through mixed visual and audio media. Electronic Visualisation and the Arts (EVA 2012), London, UK. British Computer Society, London.

2011

• Peebles, D. (2011). The effect of graphical format and instruction on the interpretation of three-variable bar and line graphs. Project report submitted to the Higher Education Academy Psychology Network


• Ali, N. & Peebles, D. (2011). The different effects of thinking aloud and writing on graph comprehension. In L. Carlson, C. Holscher, & T. Shipley (Eds.). Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.


• Peebles, D., Cooper, R. P., & Howes, A. (2011). Editorial. Cognitive Systems Research. 12. 83.


• Ali, A., Ingleby, M., & Peebles, D. (2011). Anglophone perceptions of Arabic syllable structure. In C. E. Cairns and E. Raimy (Eds.) Handbook of the Syllable, pp. 329-352. Leiden, The Netherlands: Brill. DOI: 10.1163/ej.9789004187405.i-464.93

2010

• Peebles, D. & Banks, A. P. (2010). Modelling dynamic decision making with the ACT-R cognitive architecture. Journal of Artificial General Intelligence, 2(2), 52-68.


• Davies, C. & Peebles, D. (2010). Spaces or scenes: Map-based orientation in urban environments. Spatial Cognition and Computation, 10, 135-156.

2009

• Howes, A., Peebles, D. & Cooper, R. P. (Eds). (2009). Proceedings of the 9th International Conference on Cognitive Modeling - ICCM2009. Manchester, UK.


• Peebles, D. & Ali, N. (2009). Differences in comprehensibility between three-variable bar and line graphs. In N. Taatgen, H. van Rijn, J. Nerbonne & L. Schomaker (Eds.). Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.


• Peebles, D. & Davies, C. (2009). A process model of map-based orientation in urban environments. Project report submitted to the Ordnance Survey.

2008

• Peebles, D. (2008). The effect of emergent features on judgments of quantity in configural and separable displays. Journal of Experimental Psychology: Applied, 14, 85-100.


• Cox, A.L. & Peebles, D. (2008). Cognitive Modelling in HCI Research. In P. A. Cairns, & A. L. Cox. (Eds.). Research Methods for Human Computer Interaction. Cambridge. Cambridge University Press.

2007

• Peebles, D., Davies, C., and Mora, R. (2007). Effects of geometry, landmarks and orientation strategies in the 'drop-off' orientation task. In S. Winter, M. Duckham, L. Kulik, & B. Kuipers (Eds). Spatial Information Theory. Springer.


• Davies, C., & Peebles, D. (2007) Strategies for orientation: The role of 3D landmark salience and map alignment. In Proceedings of the Twenty-Ninth Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.


• Ropar, D., & Peebles, D. (2007). Sorting preference in children with autism: The dominance of concrete features. Journal of Autism and Developmental Disorders, 37, 270-280.

2006

• Davies, C., Mora, R. and Peebles, D. (2006) Isovists for orientation: Can space syntax help us predict directional confusion? In Proceedings of the 'Space Syntax and Spatial Cognition' workshop, Spatial Cognition 2006, Bremen, Germany, 24 September 2006.


• Peebles, D. & Cox, A.L. (2006) Modelling interactive behaviour with a rational cognitive architecture. In Zaphiris, P. & Kurniawan, S. (Eds.). Human Computer Interaction Research in Web Design and Evaluation. London. Idea Group Inc. Reprinted in E. Szewczak. (Ed.). (2008). Selected Readings on the Human Side of Information Technology. IGI Global.

2004

• Peebles, D., & Bothell, D. (2004). Modelling performance in the Sustained Attention to Response Task. In M. Lovett, C. D. Schunn, C. Lebiere & P. Munro (Eds.). Proceedings of the Sixth International Conference on Cognitive Modeling. Mahwah, NJ: Lawrence Erlbaum.


• Peebles, D. (2004). Distortions of perceptual judgement in diagrammatic representations. In K. Forbus, D. Gentner & T. Regier (Eds.). Proceedings of the Twenty Sixth Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum.

2003

• Peebles, D., & Cheng, P. C.-H. (2003). Modeling the effect of task and graphical representation on response latency in a graph reading task. Human Factors, 45, 28-46. Winner of the Jerome H. Ely Human Factors Article Award for the most outstanding article in the 2003 volume of Human Factors.

2002

• Peebles, D., & Cheng, P. C.-H. (2002). Extending task analytic models of graph-based reasoning: A cognitive model of problem solving with Cartesian graphs in ACT-R/PM. Cognitive Systems Research, 3, 77-86.

2001

• Peebles, D., & Cheng, P. C.-H. (2001). Graph-based reasoning: From task analysis to cognitive explanation. In J. D. Moore & K. Stenning. (Eds.). Proceedings of the Twenty Third Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum.


• Peebles, D., & Cheng, P. C.-H. (2001). Extending task analytic models of graph-based reasoning: A cognitive model of problem solving with Cartesian graphs in ACT-R/PM. In E. M. Altmann, A. Cleermans, C. D. Schunn & W. D. Gray. (Eds.). Proceedings of the Fourth International Conference on Cognitive Modeling. Mahwah, NJ: Lawrence Erlbaum.

2000

• Peebles, D. (2000). Review of The MIT Encyclopedia of the Cognitive Sciences. Perception, 29 (5), 628-629.

1999

• Peebles, D., Cheng, P. C.-H., & Shadbolt, N. R. (1999). Multiple processes in graph-based reasoning. In M. Hahn, & S. C. Stoness (Eds.). Proceedings of the Twenty First Annual Conference of the Cognitive Science Society. Mahwah, NJ : Lawrence Erlbaum.


• Cupit, J., Shadbolt, N., Cheng, P. C.-H., & Peebles, D. (1999). Compiling ontologies into structured views and interviews: The design of a graph drawing tool for knowledge elicitation. Twelfth Workshop on Knowledge Acquisition, Modeling and Management, Banff , Alberta , Canada (KAW'99).


• Peebles, D. & Lamberts, K. (1999). A connectionist model of categorization response times. In D. Heinke, G. W. Humphreys, & A. Olson. (Eds.), Connectionist Models in Cognitive Neuroscience. London, Springer-Verlag.

1997

• Peebles, D. (1997). The effect of stimulus frequency on classification accuracy and response time. Unpublished doctoral dissertation. University of Birmingham, Birmingham, 1997.