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Downloaded from Inmoov, but Some Were Created Independently Determining the effect of human cognitive biases in social robots for human-robot interactions Mriganka Biswas A thesis submitted in partial fulfilment of the requirements of the University of Lincoln for the degree of Doctor of Philosophy Doctor of Philosophy 2016 I would like to dedicate this thesis to my loving parents ii Declaration I hereby declare that except where specific reference is made to the work of others, the contents of this dissertation are original and have not been submitted in whole or in part for consideration for any other degree or qualification in this, or any other university. This dissertation is my own work and contains nothing which is the outcome of work done in collaboration. This research has been documented, in part, within the following publications: Journal articles: 1. Biswas, M. and Murray, J. (2017) The effects of cognitive biases and imperfectness in long- term robot-human interactions: case studies using five cognitive biases on three robots. Cognitive Systems Research Journal, 43(C) 266-290. Available from doi:10.1016/j.cogsys.2016.07.007 [accessed 14 May 2017]. 2. Biswas, M. and Murray, J. (2016) Can cognitive biases in robots make more ‘likeable' human- robot interactions than the robots without such biases: case studies using five biases on humanoid robot. International Journal of Artificial Life Research (IJALR), 6(1) 1-29. Available from doi:10.4018/IJALR.2016010101 [accessed 14 May 2017]. Conference papers: 1. Biswas, M. and Murray, J. (2014) Effect of cognitive biases on human-robot interaction: a case study of a robot's misattribution. In: 23rd IEEE international symposium on robot and human interactive communication, IEEE RO-MAN 2014, Edinburgh, UK, 25-29 August. 2. Biswas, M. and Murray, J. (2015) Robotic Companionship: how Forgetfulness Affects Long- Term Human-Robot Interaction. In: 8th international conference on intelligent robotics and applications, Portsmouth, UK, 14 August. 3. Biswas, M. and Murray, J. (2015) Towards an imperfect robot for long-term companionship: case studies using cognitive biases. In: IEEE/RSJ international conference on intelligent robots and systems, Hamburg, Germany, 28 September – 2 October. iii 4. Biswas, M. and Murray, J. (2016), Robots that refuse to admit losing – a case study in game playing using self-serving bias in the humanoid robot MARC. In: 9th international conference on intelligent robotics and applications, Tokyo, Japan, 16 August. 5. Biswas, M. and Murray, J. (2016) The influences of ‘self-serving’ bias in robot-human companionship: case studies using the humanoid robot MARC. Workshop on behaviour adaptation, interaction and learning for assistive robotics. In: RO-MAN 2016, New York, US, 14 May 2017. 6. Biswas, M. and Murray, J. (2016) The effects of cognitive biases in long-term human-robot interactions: case studies using three cognitive biases on MARC the humanoid robot. In: The eighth international conference on social robotics, Kansas City, USA, 1-3 November. Posters: 1. Biswas, M. and Murray, J. (2013) Building a long term human-robot relationship: how emotional interaction plays a key role in attachment. In: Fourth EUCogIII members conference, 23-24 October, Falmer/Brighton. 2. Biswas, M. and Murray, J. (2013) Developing long-term human-robot interaction. HFR2013, 25-26 September, Rome. 3. Biswas, M. and Murray, J. (2014) A model for long-term human-robot interaction and relationships in a companion robot. In: Sixth EUCogIII members conference, 17-18 October, Genoa. iv Acknowledgements I would like to express my special thanks to my supervisor Dr John Murray. You have been a tremendous mentor for me. I would like to thank you for encouraging and guiding my research and for allowing me to grow as a research scientist. Your advice on both research as well as on my career have been invaluable. I would like to express my gratitude to my family for their support and encouragement over the years. Words cannot express how grateful I am to my mother, Namita Biswas and father, Sasanka Sekhar Biswas for all of the sacrifices they’ve made on my behalf. Your prayer for me was what sustained me this far. I would also like to thank to my beloved wife, Payel. Thank you for supporting me for everything. v Abstract The research presented in this thesis describes a model for aiding human-robot interactions based on the principle of showing behaviours which are created based on 'human' cognitive biases by a robot in human-robot interactions. The aim of this work is to study how cognitive biases can affect human-robot interactions in the long term. Currently, most human-robot interactions are based on a set of well-ordered and structured rules, which repeat regardless of the person or social situation. This trend tends to provide an unrealistic interaction, which can make difficult for humans to relate ‘naturally’ with the social robot after a number of relations. The main focus of these interactions is that the social robot shows a very structured set of behaviours and, as such, acts unnaturally and mechanical in terms of social interactions. On the other hand, fallible behaviours (e.g. forgetfulness, inability to understand other’ emotions, bragging, blaming others) are common behaviours in humans and can be seen in regular social interactions. Some of these fallible behaviours are caused by the various cognitive biases. Researchers studied and developed various humanlike skills (e.g. personality, emotions expressions, traits) in social robots to make their behaviours more humanlike, and as a result, social robots can perform various humanlike actions, such as walking, talking, gazing or emotional expression. But common human behaviours such as forgetfulness, inability to understand other emotions, bragging or blaming are not present in the current social robots; such behaviours which exist and influence people have not been explored in social robots. The study presented in this thesis developed five cognitive biases in three different robots in four separate experiments to understand the influences of such cognitive biases in human–robot interactions. The results show that participants initially liked to interact with the robot with cognitive biased behaviours more than the robot without such behaviours. In my first two experiments, the robots (e.g., ERWIN, MyKeepon) interacted with the participants using a single bias (i.e., misattribution and empathy gap) cognitive biases accordingly, and participants enjoyed the interactions using such bias effects: for example, forgetfulness, source confusions, always showing exaggerated happiness or sadness and so on in the robots. In my later experiments, participants interacted with the robot (e.g., MARC) three times, with a time interval between two interactions, and results show that the likeness the interactions where the robot shows biased behaviours decreases less than the interactions where the robot did not show any biased behaviours. In the current thesis, I describe the investigations of these traits of forgetfulness, the inability to understand others’ emotions, and bragging and blaming behaviours, which are influenced by cognitive biases, and I also analyse people’s responses to robots displaying such biased behaviours in human–robot interactions. vi Contents Declaration ........................................................................................................................................ iii Acknowledgements ............................................................................................................................ v Abstract.............................................................................................................................................. vi Contents ............................................................................................................................................ vii List of Figures ..................................................................................................................................... x List of Tables .................................................................................................................................... xii Chapter 1 Introduction ..................................................................................................................... 1 1.1 Outline ..................................................................................................................................... 1 1.2 Motivation ............................................................................................................................... 2 1.2.1 Cognitive bias ..................................................................................................................... 4 1.3 Hypothesis ............................................................................................................................... 7 1.4 Objectives ............................................................................................................................... 8 1.5 Thesis organisation ................................................................................................................. 9 Chapter 2 Social Robots and Human–Robot Interaction ........................................................... 11 2.1 The social robots ................................................................................................................... 11 2.2 The importance of social robots ...........................................................................................
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