Publications

2024

  1. Revision operators with compact representations, 2024 Pavlos Peppas, Mary-Anne Williams, Grigoris Antoniou, Artificial Intelligence Journal, Volume 329. Number 1  journal  Artificial Intelligence.
  2. Simulation Evidence of Trust Calibration: Using POMDP with Signal Detection Theory to Adapt Agent Features for Optimised Task Outcome During Human-Agent Collaboration, S Herse, J Vitale, M-A Williams, International Journal of Social Robotics, 1-23. Journal Ranking Q1
2023

    1. Using agent features to influence user trust, decision making and task outcome during human-agent collaboration, S Herse, J Vitale, MA Williams, International Journal of Human–Computer Interaction 39 (9), 1740-1761. Journal Ranking Q1
    2. Generalizing Parikh's Criterion for Relevance-Sensitive Belief Revision, T Aravanis, P Peppas, MA Williams, Journal of Logic and Computation  30 (5), 1125-1142. Oxford University Press Top 10 journal in Logic.

    2022

    1. An in-the-wild study to find type of questions people ask to a social robot providing question-answering service. SA Raza, J Vitale, M Tonkin, B Johnston, R Billingsley, S Herse, Intelligent Service Robotics 15 (3), 411-426

    2021 

    1. Computational emotion models: a thematic review, S Ojha, J Vitale, MA Williams, International Journal of Social Robotics 13, 1253-1279 Journal Ranking Q1
    2. Simplified pain matrix method for artificial pain activation embedded into robot framework, M Anshar, MA Williams, International Journal of Social Robotics 13, 187–195 (2021). Journal Ranking Q1
    3. Using trust to determine user decision making & task outcome during a human-agent collaborative task, S Herse, J Vitale, B Johnston, MA Williams, Proceedings of ACM/IEEE International Conference on Human-Robot Interaction, pages 73-82 (2021) Highly Prestigious Conference #1 in Human-Robot Interaction.
    4. Designing Human-Robot Interaction with Social Intelligence, MA Williams, Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction pages 3-4 (2021) Highly Prestigious Conference #1 in Human-Robot Interaction
    5. Would you trust a robot with your mental health? The interaction of emotion and logic in persuasive backfiring, S Alam, B Johnston, J Vitale, MA Williams, in the Proceedings of the 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN). Oldest and leading conference in Human-Robot Interaction.
    6. Skill-driven recommendations for job transition pathways, N Dawson, MA Williams, MA Rizoiu, PLoS One 16 (8), e0254722
    7. Explainable Artificial Intelligence (Chapter 16), MA Williams, Research Handbook on Big Data Law, Roland Vogl (editor) Stanford University 544 pages. Invited Chapter.
    8. An investigation of parametrized difference revision operators, T Aravanis, P Peppas, MA Williams, Annals of Mathematics and Artificial Intelligence 89, 7-28 (2021) Highly specialist journal with prestigious international editorial board 
    9. How AI can help choose your next career and stay ahead of automation,Nik Dawson, Marian-Andrei Rizoiu and Mary-Anne Williams, The Conversation, August 5, 2021.

    2020

    1. Incompatibilities between Iterated and Relevance-Sensitive Belief Revision,Theofanis Aravanis, Pavlos Peppas and Mary-Anne Williams, Journal of Artificial Intelligence Research 69, 85-108 
    2. Modelling Belief-Revision Functions at Extended Languages, Theofanis Aravanis, Pavlos Peppas and Mary-Anne Williams, 2020 European Conference on Artificial Intelligence.
    3. Human feedback as action assignment in interactive reinforcement learning, SA Raza and MA Williams, ACM Transactions on Autonomous and Adaptive Systems (TAAS) 14 (4), 1-24
    4. A Machine Learning Approach Predicting Skill Shortages in Labor Markets: A Machine Learning Approach,  Nikolas Dawson, Marian-Andrei Rizoiu, Benjamin Johnston and Mary-Anne Williams, 2020 IEEE International Conference on Big Data.
    5. Advanced Robotics 34 (24) 1545-1590, Tetsunari Inamura, Amit Kumar Pandey, Swagat Kumar, Mary-Anne Williams, John-John Cabibihan & Laxmidhar Behera, Special Issue on Robot and Human Interactive Communication 2020 (Part II), Advanced Robotics, 34:24, 1545, DOI: 10.1080/01691864.2020.1854936
    6. Advanced Robotics 34 (20) 1279-1333, Tetsunari Inamura, Amit Kumar Pandey, Swagat Kumar, Mary-Anne Williams, John-John Cabibihan & Laxmidhar Behera, Special Issue on Robot and Human Interactive Communication 2020, Advanced Robotics, 34:20, 1279, DOI: 10.1080/01691864.2020.1831718

    2019

    1. Data Science and Analytics Skills and Occupations in Australia, Nikolas Dawson, Marian-Andrei Rizoiu, Benjamin Johnston and Mary-Anne Williams, IEEE International Conference on Big Data, pages:1637 - 1643
    2. Observations on the Darwiche and Pearl's Approach for Iterated Belief Revision,  Theofanis Aravanis, Pavlos Peppas, and Mary-Anne Williams. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019 pp1509 - 1515.
    3. Privacy First: Designing Responsible and Inclusive Social Robot Applications for in the Wild Studies. Meg Tonkin, Jonathan Vitale, Sarita Herse, Syed Ali Raza, Sri Madhisetty, Le Kang, The Duc Vu, Benjamin Johnston and Mary-Anne Williams. In: 28th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2019  pp. 1-8.
    4. Measuring Human Emotion in Short Documents to Improve Social Robot and Agent Interactions, Canadian Conference on Artificial Intelligence 2019: Advances in Artificial Intelligence pp 29-41, with David Skillicorn, N. Alsadhan, Richard Billingsley.
    5. How to manage privacy in photos after publication' ICEIS 2019 - Proceedings of the 21st International Conference on Enterprise Information Systems, pp. 162-168. 2019 with Madhisetty, S,, Massy-Greene, J, Franco, L & El Khoury,
    6. The role of trust and control in managing privacy when photos and videos are stored or shared, Advances in Intelligent Systems and Computing, pp. 127-140, 2019 with Sri Madhisetty.
    7. Managing privacy through key performance indicators when photos and videos are shared via social media, Advances in Intelligent Systems and Computing, pp. 1103-1117, 2019 with Sri Madhisetty.
    8. UTS Unleashed! RoboCup@Home SSPL Champions 2019, in Proceedings of the International RoboCup Symposium, Springer, 2019 with Sammy Pfeiffer, Daniel Ebrahimian, Sarita Herse, Tran Nhut Le, Suwen Leong, Bethany Lu, Katie Powell, Syed Ali Raza, Tian Sang, Meg Tonkin, The Duc, Vu, Qijun Yang, Richard Billingsley, Jesse Clark, Benjamin Johnston, Srinivas Madhisetty, Neil McLaren, Pavlos Peppas and Jonathan Vitale.

      9. 2018


  1. United Nations Report on the Impact of Artificial Intelligence with McKinsey, IBM, AI Policy Hub, and others.
  2. Evolving robot empathy towards humans with motor disabilities through artificial pain generation, M Anshar, and M-A Williams, AIMS Journal of Neuroscience, 2018
  3. Parametrised Difference Revision, Pavlos Peppas and Mary-Anne Williams, 16th International Conference on Principles of Knowledge Representation and Reasoning (KR2018)
  4. Do You Trust Me, Blindly? Factors Influencing Trust Towards a Robot Recommender System, Sarita Herse, Jonathan Vitale, Meg Tonkin, Daniel Ebrahimian, Suman Ojha, Benjamin Johnston, William Judge, and Mary-Anne Williams, IEEE International Conference on Robot and Human Interactive Communication, 2018. This paper explores how robots can help robots trust them.
  5. Be More Transparent and Users Will Like You: A Robot Privacy and User Experience Design Experiment, Jonathan Vitale, Meg Tonkin. Sarita Herse, Suman Ojha, Jesse Clark, Mary-Anne Williams, Xun Wang, William Judge in Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI-18) and will be available in the ACM Digital Library. The leading conference on Human-Robot Interaction. This paper reports new results on privacy research in human-robot interaction undertaken with the Commonwealth Bank 
  6. Design Methodology for the UX of HRI: Example Study of a Commercial Social Robot at an Airport  (2018).  Meg Tonkin, Sarita Herse, Jonathan Vitale, Mary-Anne Williams, Xun Wang, William Judge in Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI-18) and will be available in the ACM Digital Library. The leading conference on Human-Robot Interaction. This paper provides an innovative methodology for HRI UX validated in experiments with the Commonwealth Bank of Australia and Sydney International Airport.
  7. Avoid being the Turkey: How big data analytics changes the game of strategy in times of ambiguity and uncertainty, Mark van Rijmenam, Tatiana Erekhinskaya, Jochen Schweitzer, and Mary-Anne Williams, Long Range Planning Journal.
  8. Event Boards as Tools for Holistic AI, Peter Gärdenfors, Mary-Anne Williams, Benjamin Johnston, Richard Billingsley, Jonathan Vitale, Pavlos Peppas and Jesse Clark, AIC2018: 6th International Workshop on Artificial Intelligence and Cognition.

2017

gUTSy on baby duty
gUTSy on baby duty
Ed Feigenbaum Turing Award
Ed Feigenbaum Turing Award
CBA and UTS students
CBA and UTS students

  1. Epistemic-entrenchment Characterization of Parikh's Axiom, 

    Theofanis Aravanis, Pavlos Peppas, Mary-Anne Williams (2017) in 

    Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence IJCAI-17, p772-778.

  2. Embodiment, Privacy and Social Robots: May I remember you?, International Conference on Social Robotics, Meg Tonkin, Jonathan Vitale, Suman Ojha, Jesse Clark, Sammy Pfeiffer, William Judge, Xun Wang, and Mary-Anne Williams
  3. Processing The Essence of Ethical Reasoning in Robot-Emotion, International Journal of Social Robotics, Suman Ojha · Mary-Anne Williams · Benjamin Johnston.
  4. A Domain-Independent Approach of Cognitive Appraisal Augmented by Higher Cognitive Layer of Ethical Reasoning, in the Proceedings of the 39th Annual Meeting of the Cognitive Science Society, CogSci 2017: Computational foundations of Cognition, Suman Ojha, Jonathan Vitale, Mary-Anne Williams.
  5. Facial Motor Information is Sufficient for Identity Recognition, Proceedings of the 39th Annual Meeting of the Cognitive Science Society, CogSci 2017: Computational foundations of Cognition, Jonathan Vitale, Benjamin Johnston, Mary-Anne Williams. 
  6. Robot Authority and Human Obedience: A Study of Human Behaviour using a Robot Security Guard, Twelfth ACM/IEEE International Conference on Human Robot Interaction. IEEE Press, Siddharth Agrawal and Mary-Anne Williams.
  7. Potential Based Reward Shaping Using Learning to Rank, Twelfth ACM/IEEE International Conference on Human Robot Interaction. IEEE Press, Syed Ali Raza and Mary-Anne Williams.
  8. Unconventional Formats of Background Knowledge from a Human Teacher in Reward Shaping, Twelfth ACM/IEEE International Conference on Human Robot Interaction, HRI Pioneers 2017 Workshop. IEEE Press. Syed Ali Raza and Mary-Anne Williams.
  9. Emotion in Robot Decision Making, in Advances in Intelligent Systems and Computing Vol. 447 (pp. 221-232). Rony Novianto and Mary-Anne Williams. 

2016

  1. Williams, M. A. (2016). Decision-theoretic human-robot interaction: Designing reasonable and rational robot behaviour. In Lecture Notes in Computer Science  Vol. 9979 LNAI (pp. 72-82). 
  2. Surden, H. and Williams, M-A., Self-Driving Cars, Predictability, and Law, Cardozo Law Review, Volume 38 Nov 2016 No 1, p212 - 182. A top law journal;  the paper gained a place on the top ten papers downloaded in legal scholarship on SSRN.
  3. Abidi, S., Piccardi, M., & Williams, M. (2016). Static Action Recognition by Efficient Greedy Inference. In Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision (pp. 1-8). Piscataway, NJ, USA: IEEE. 
  4. Raza, S. A., Clark, J., & Williams, M. (2016). On Designing Socially Acceptable Reward Shaping. In A. Agah, J. J. Cabibihan, A. M. Howard, M. A. Salichs, & H. He (Eds.), Social Robotics (pp. 860-869). Kansas City, MO, USA: Springer.  
  5. Raza, R. A., Williams, M-A, & Johnston, B. (2016). Reward from Demonstration in Interactive Reinforcement Learning. In Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference.
  6. Vitale, J., Williams, M. -A., & Johnston, B. (2016). The face-space duality hypothesis: a computational model. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 514-519). Austin, TX: Cognitive Science Society. Retrieved from https://mindmodeling.org/cogsci2016/
  7. Ojha, S., & Williams, M. A. (2016). Ethically-Guided Emotional Responses for Social Robots: Should I Be Angry? In International Conference on Social Robotics. Kansas City, USA. Retrieved from https://link.springer.com/chapter/10.1007/978-3-319-47437-3_23
  8. Romat, H., Williams, M. -A., Wang, X., Johnston, B., Bard, H., & IEEE. (2016). Natural Human-Robot Interaction Using Social Cues. In Proceedings of the HRI '16 The Eleventh ACM/IEEE International Conference on Human Robot Interaction (pp. 503-504). USA: ACM.
  9. Peppas, P., & Williams, M. A. (2016). Kinetic consistency and relevance in belief revision. In Lecture Notes in Artificial Intelligence Vol. 10021 LNAI Proceedings of the European Conference on Logic (JELIA) pp. 401-414. 
  10. Romat, H., Williams, M. -A., Wang, X., Johnston, B., Bard, H., & ACM. (2016). Natural Human-Robot Interaction Using Social Cues. In Eleventh ACM/IEEE International Conference On Human Robot Interaction (Hri'16) (pp. 503-504).
  11. Raza, R.A., Johnston, B., and Williams, M-A., Reward from Demonstration in Interactive Reinforcement Learning, Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, Association for the Advancement of Artificial Intelligence AAAI Publishing, Menlo Park, 2016
  12. Raza, S. A., Clark, J., & Williams, M. (2016). On Designing Socially Acceptable Reward Shaping. In A. Agah, J. J. Cabibihan, A. M. Howard, M. A. Salichs, & H. He (Eds.), Social Robotics (pp. 860-869). Kansas City, MO, USA: Springer.  

2015

  1. Peppas, P., Williams, M-A, Chopra, S. and Foo, N., 2015,. "Relevance in Belief Revision", Artificial Intelligence Journal, vol. 229, pp. 126-138
  2. Anshar, M. and Williams, M.A. 2015, 'Evolving synthetic pain into an adaptive self-awareness framework for robots', Biologically Inspired Cognitive Architectures Journal.
  3. Ramezani, N. & Williams, M-A. 2015, 'Smooth robot motion with an Optimal Redundancy Resolution for PR2 robot based on an analytic inverse kinematic solution', IEEE-RAS 15th International Conference on, IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids-2015) pp. 338-345

2014

  1. Vitale, J., Williams, M.-.A., Johnston, B. & Boccignone, G. 2014, 'Affective facial expression processing via simulation: A probabilistic model', Biologically Inspired Cognitive Architectures, vol. 10, pp. 30-41.
  2. Cabibihan, J.-.J., Williams, M.-.A. & Simmons, R. 2014, 'When Robots Engage Humans', International Journal of Social Robotics, vol. 6, no. 3, pp. 311-313.
  3. Williams, M-A. & Peppas, P. 2014, 'Constructive models for contraction with intransitive plausibility indifference', Logics in Artificial Intelligence - Lecture Notes in Computer Science, 14th European Conference on Logics in Artificial Intelligence (JELIA), Springer Verlag, Madeira, Portugal, pp. 355-367.
  4. Wang, X., Williams, M.-.A., Gardenfors, P., Vitale, J., Abidi, S., Johnston, B., Kuipers, B. & Huang, A. 2014, 'Directing human attention with pointing', Robot and Human Interactive Communication, 2014 RO-MAN: The 23rd IEEE International Symposium on Robot and Human Interactive Communication,  pp. 174-179.
  5. P. Peppas, and M.-A. Williams, "Belief Change and Semiorders", Proceedings of the 14th International Conference on the Principles of Knowledge Representation and Reasoning (KR2014).
  6. Novianto, R. and Williams, M-A. 2014, 'Operant Conditioning in ASMO Cognitive Architecture', BICA 2014. 5th Annual International Conference on Biologically Inspired Cognitive Architectures, Elsevier, Massachusetts Institute of Technology, Cambridge, MA, USA, pp. 404-411.
  7. Novianto, R., Williams, M-A., Gärdenfors, P. & Wightwick, G. 2014, 'Classical conditioning in social robots', Lecture Notes in Computer Science, Springer Verlag, Germany, pp. 279-289.