Publications

2017

  1. 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
  2. Processing The Essence of Ethical Reasoning in Robot-Emotion, International Journal of Social Robotics, Suman Ojha · Mary-Anne Williams · Benjamin Johnston.
  3. 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.
  4. 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. 
  5. 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.
  6. 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.
  7. 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.
  8. 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, to appear. This is a top law journal and the paper gain a top 10 place on the top ten papers downloaded in legal scholarship on SSRN in the first month.
  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 http://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 Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10021 LNAI (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. Abidi, Piccardi, M. and Williams M-A 2016, 'Static Action Recognition by Efficient Greedy Inference', Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016 IEEE Winter Conference on Applications of Computer Vision, IEEE, USA.
  13. 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', Humanoid Robots (Humanoids), 2015 IEEE-RAS 15th International Conference on, IEEE-RAS 15th International Conference on Humanoid Robots, IEEE, Seoul, Korea, 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 (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14th European Conference on Logics in Artificial Intelligence, 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, The 23rd IEEE International Symposium on Robot and Human Interactive Communication, IEEE, Edinburgh, Scotland, 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), Vienna, Austria, July 2014.
  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, Biologically Inspired Cognitive Architecture, 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 (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, Germany, pp. 279-289.