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12 - Artificial emotions and machine consciousness

Published online by Cambridge University Press:  05 July 2014

Matthias Scheutz
Affiliation:
Tufts University
Keith Frankish
Affiliation:
The Open University, Milton Keynes
William M. Ramsey
Affiliation:
University of Nevada, Las Vegas
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Summary

Introduction

Over the last decade, interest in artificial emotions and machine consciousness has noticeably increased in artificial intelligence (AI), as witnessed by a number of specialized conferences and workshops dedicated to these themes. This interest is in part based on the recognition that emotions and consciousness have useful roles in humans and other animals, and that understanding these roles and implementing models of them on computers might help in making artificial agents smarter. But can machines even have emotions and be conscious, and if so, how could we go about designing such machines?

The goal of this chapter is to present an overview of the work in AI on emotions and machine consciousness, with an eye toward answering these questions. Starting with a brief philosophical perspective on emotions and machine consciousness to frame the work, the chapter first focuses on artificial emotions, and then moves on to machine consciousness – reflecting the fact that emotions and consciousness have been treated independently and by different communities in AI. The chapter concludes by discussing philosophical implications of AI research on emotions and consciousness.

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Chapter
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Publisher: Cambridge University Press
Print publication year: 2014

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References

Scherer, K. R., Bänziger, T., and Roesch, E. B. (2010). Blueprint for Affective Computing: A Sourcebook. Oxford University Press. A comprehensive collection of research chapters on the various aspects of emotions and current emotion models, ranging from theoretical frameworks to specific algorithms for implementing affectively competent artificial agents.Google Scholar
Wallach, W. and Allen, C. (2009). Moral Machines: Teaching Robots Right from Wrong. Oxford University Press. A great foray into the problems associated with building intelligent autonomous robots and an appeal to implement moral decision making in artificial agents.CrossRefGoogle Scholar
The International Journal of Synthetic Emotions (IGI). A good resource for research papers on different models and implementations of artificial emotions.
The International Journal of Machine Consciousness (World Scientific). A great resource for the latest research papers on the emergent field of machine consciousness.
Aleksander, I. and Dunmall, B. (2003). Axioms and tests for the presence of minimal consciousness in agents, in Holland, O. (ed.), Machine Consciousness (pp. 7–18). New York: Imprint Academic.Google Scholar
Alexandrov, Y. I. and Sams, M. E. (2005). Emotion and consciousness: Ends of a continuum, Cognitive Brain Research 25: 387–405.CrossRefGoogle ScholarPubMed
Anderson, J. R. (1993). Rules of the Mind. Mahwah, NJ: Erlbaum.Google Scholar
Angel, L. (1989). How to Build a Conscious Machine. Boulder, CO: Westview Press.Google Scholar
Baars, B. J. (1997). In the Theater of Consciousness: The Workspace of the Mind. New York: Oxford University Press.CrossRefGoogle Scholar
Balkenius, C. and Morén, J. (2001). Emotional learning: A computational model of the amygdala, Cybernetics and Systems 32: 611–36.CrossRefGoogle Scholar
Bates, J., Loyall, A. B., and Reilly, W. S. (1994). An architecture for action, emotion, and social behavior, in Castelfranchi, C. and Werner, E. (eds.), Artificial Social Systems: 4th European Workshop on Modelling Autonomous Agents in a Multi-Agent World (MAAMAW ’92) (pp. 55–68). Berlin: Springer.CrossRefGoogle Scholar
Blair, H. T., Tinkelman, A., Moita, M. A. P., and LeDoux, J. E. (2003). Associative plasticity in neurons of the lateral amygdala during auditory fear conditioning, Annals of the New York Academy of Sciences 985: 485–7.CrossRefGoogle ScholarPubMed
Brave, S. and Nass, C. (2003). Emotion in human–computer interaction, in Jacko, J. A. and Sears, A. (eds.), The Human–Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications (pp. 81–96). Mahwah, NJ: Erlbaum.Google Scholar
Cañamero, D. (1997). Modeling motivations and emotions as a basis for intelligent behavior, in Johnson, W. L. (ed.), Proceedings of the First International Conference on Autonomous Agents (agents’97) (pp. 148–55). New York: ACM Press.CrossRefGoogle Scholar
Cosmides, L. and Tooby, J. (2004). Evolutionary psychology and the emotions, in Lewis, M. and Haviland-Jones, J. M. (eds.), Handbook of Emotions (2nd edn.) (pp. 91–115). New York: Guilford Press.Google Scholar
Fanselow, M. S. and Gale, G. D. (2003). The amygdala, fear, and memory, Annals of the New York Academy of Sciences 985: 125–34.CrossRefGoogle Scholar
Franklin, S. (2000). Modeling consciousness and cognition in software agents, in Taatgen, N., Aasman, J. (eds.), Proceedings of the 3rd International Conference on Cognitive Modeling (pp. 100–9). Veenendal, The Netherlands: Universal Press.Google Scholar
Franklin, S., Kelemen, A., and McCauley, L. (1998). Ida: A cognitive agent architecture, in IEEE International Conference on Systems, Man, and Cybernetics, vol. 3 (pp. 2646–51).Google Scholar
Frijda, N. H. (1994). Varieties of affect: Emotions and episodes, moods, and sentiments, in Ekman, P. and Davidson, R. J. (eds.), The Nature of Emotion: Fundamental Questions (pp. 59–67). New York: Oxford University Press.Google Scholar
Gadanho, S.C. (2003). Learning behavior-selection by emotions and cognition in a multi-goal robot task, Journal of Machine Learning Research 4: 385–412.Google Scholar
Gratch, J. and Marsella, S. (2004a). A domain-independent framework for modeling emotion, Cognitive Systems Research 5: 269–306.CrossRefGoogle Scholar
Gratch, J. and Marsella, S.. (2004b). Evaluating the modeling and use of emotion in virtual humans, in Proceedings of the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems, vol. 1 (pp. 320–7).Google Scholar
Gratch, J. and Marsella, S.. (2009). EMA: A process model of appraisal dynamics, Cognitive Systems Research 10: 70–90.Google Scholar
Griffiths, P. E. (1997). What Emotions Really Are: The Problem of Psychological Categories. Chicago University Press.CrossRefGoogle Scholar
Grossberg, S. and Schmajuk, N. (1987). Neural dynamics of attentionally-modulated Pavlovian conditioning: Conditioned reinforcement, inhibition, and opponent processing, Psychobiology 15: 195–240.Google Scholar
Haikonen, P. O. (2003). The Cognitive Approach to Conscious Machines. Exeter: Imprint Academic.Google Scholar
Holland, O. (ed.) (2003). Machine Consciousness. New York: Imprint Academic.
Hoque, M., McDuff, D., and Picard, R. (2012). Exploring temporal patterns towards classifying frustrated and delighted smiles, IEEE Transactions on Affective Computing 3: 323–34.CrossRefGoogle Scholar
Ichise, R., Shapiro, D. G., and Langley, P. (2002). Learning hierarchical skills from observation, in Proceedings of the 5th International Conference on Discovery Science (pp. 247–58).
Kuipers, B. (2005). Consciousness: Drinking from the firehose of experience, in Proceedings of the 20th National Conference on Artificial Intelligence, vol. 3 (pp. 1298–305).Google Scholar
Laird, J. E., Newell, A., and Rosenbloom, P. S. (1987). SOAR: An architecture for general intelligence, Artificial Intelligence 33: 1–64.CrossRefGoogle Scholar
LeDoux, J. (1996). The Emotional Brain: The Mysterious Underpinnings of Emotional Life. New York: Simon and Schuster.Google Scholar
Lycan, W. G. (1987). Consciousness. Cambridge MA: MIT Press.Google Scholar
Macedo, L. and Cardoso, A. (2001). Modeling forms of surprise in an artificial agent, in Moore, J. and Stenning, K. (eds.), Proceedings of the 23rd Annual Conference of the Cognitive Science Society (pp. 588–93). Mahwah, NJ: Erlbaum.Google Scholar
Manzotti, R. (2003). A process-based architecture for an artificial conscious being, in Seibt, J. (ed.), Process Theories: Crossdisciplinary Studies in Dynamic Categories (pp. 285–312). Dordrecht: Kluwer Academic Press.CrossRefGoogle Scholar
McDermott, D. (1981). Artificial intelligence meets natural stupidity, in Haugeland, J. (ed.), Mind Design: Philosophy, Psychology, Artificial Intelligence (pp. 143–60). Cambridge, MA: MIT Press.Google Scholar
Murphy, R. R., Lisetti, C., Tardif, R., Irish, L., and Gage, A. (2002). Emotion-based control of cooperating heterogeneous mobile robots, IEEE Transactions on Robotics and Automation 18: 744–57.CrossRefGoogle Scholar
Nerb, J. and Sperba, H. (2001). Evaluation of environmental problems: A coherence model of cognition and emotion, Cognition and Emotion 4: 521–51.CrossRefGoogle Scholar
Ortony, A., Clore, G. L., and Collins, A. (1988). The Cognitive Structure of Emotions. New York: Cambridge University Press.CrossRefGoogle Scholar
Panksepp, J. (1998). Affective Neuroscience: The Foundations of Human and Animal Emotions. Oxford University Press.Google Scholar
Pfeifer, R. (1988). Artificial intelligence models of emotion, in Hamilton, V., Bower, G. H., and Frijda, N. H. (eds.), Cognitive Perspectives on Emotion and Motivation (pp. 287–320). Dordrecht: Kluwer Academic Publishers.CrossRefGoogle Scholar
Picard, R. (1997). Affective Computing. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Putnam, H. (1964). Robots: Machines or artificially created life? The Journal of Philosophy 61: 668–91.Google Scholar
Rickel, J., Marsella, S., Gratch, J., Hill, R., Traum, D., and Swartout, W. (2002). Towards a new generation of virtual humans for interactive experiences, IEEE Intelligent Systems, 17(4): 32–8.CrossRefGoogle Scholar
Sanz, R., López, I., and Hernández, C. (2007). Self-awareness in real-time cognitive control architectures, in Chella, A. and Manzotti, R. (eds.), AI and Consciousness: Theoretical Foundations and Current Approaches: Papers from the AAAI Fall Symposium (pp. 135–40). Menlo Park, CA: AAAI Press.Google Scholar
Scheutz, M. (2001a). Causal versus computational complexity, Minds and Machines 11: 534–66.CrossRefGoogle Scholar
Scheutz, M.. (2001b). The evolution of simple affective states in multi-agent environments, in Cañamero, D. (ed.), Proceedings of AAAI Fall Symposium (pp. 123–8). Falmouth, MA: AAAI Press.Google Scholar
Scheutz, M.. (2002). Agents with or without emotions? in Weber, R. (ed.), Proceedings of the 15th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 89–94). AAAI Press.Google Scholar
Scheutz, M.. (2004). Useful roles of emotions in artificial agents: A case study from artificial life, in Proceedings of the 19th National Conference on Artifical Intelligence (pp. 42–7). AAAI Press.Google Scholar
Scheutz, M.. (2011). Architectural roles of affect and how to evaluate them in artificial agents, International Journal of Synthetic Emotions 2(2): 48–65.CrossRefGoogle Scholar
Scheutz, M., Schermerhorn, P., and Kramer, J. (2006). The utility of affect expression in natural language interactions in joint human–robot tasks, in Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction (pp. 226–33).
Searle, J. R. (1992). The Rediscovery of the Mind. Cambridge MA: MIT Press.Google Scholar
Shanahan, M. P. (2005). Consciousness, emotion, and imagination: A brain-inspired architecture for cognitive robotics, in Proceedings aisb 2005 symposium on next generation approaches to machine consciousness (pp. 26–35).
Sloman, A. and Chrisley, R. (2003). Virtual machines and consciousness, Journal of Consciousness Studies 10(4–5): 133–72.Google Scholar
Sloman, A. and Croucher, M. (1981). Why robots will have emotions, in Proceedings of the 7th International Joint Conference on AI (pp. 197–202).
Trappl, R., Petta, P., and Payr, S. (eds.) (2002). Emotions in Humans and Artifacts. Cambridge MA: MIT Press.
Turing, A. (1950). Computing machinery and intelligence, Mind 59: 433–60. Reprinted (1963) in Feigenbaum, E. A. and Feldman, J. (eds.), Computers and Thought (pp. 11–35). New York: McGraw-Hill.Google Scholar
Velásquez, J. D. (1999). When robots weep: Emotional memories and decision-making, in Proceedings of the 15th National Conference on Artificial Intelligence (pp. 70–5). Menlo Park, CA: AAAI Press.Google Scholar

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