Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-15T04:47:55.576Z Has data issue: false hasContentIssue false
  • English
  • Français

Designing emotional BDI agents: good practices and open questions

Published online by Cambridge University Press:  17 December 2019

Yanet Sánchez-López Open the ORCID record for Yanet Sánchez-López [Opens in a new window]  and
Eva Cerezo
Yanet Sánchez-López*
Affiliation:
Department of Computer Science and Systems Engineering, Aragón Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain, e-mails: ysanchezl@unizar.es; ecerezo@unizar.es
Eva Cerezo
Affiliation:
Department of Computer Science and Systems Engineering, Aragón Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain, e-mails: ysanchezl@unizar.es; ecerezo@unizar.es
Get access Rights & Permissions [Opens in a new window]

Abstract

Intelligent agents built on the basis of the BDI (belief–desire–intention) architecture are known as BDI agents. Currently, due to the increasing importance given to the affective capacities, they have evolved giving way to the BDI emotional agents. These agents are generally characterized by affective states such as emotions, mood or personality but sometimes also by affective capacities such as empathy or emotional regulation. In the paper, a review of the most relevant proposals to include emotional aspects in the design of BDI agents is presented. Both BDI formalizations and BDI architecture extensions are covered. From the review, common findings and good practices modeling affect, empathy and regulatory capacities in BDI agents, are extracted. In spite of the great advance in the area several, open questions remain and are also discussed in the paper.

Type
Review
Information
The Knowledge Engineering Review , Volume 34 , 2019 , e26
Copyright
© Cambridge University Press, 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adam, C., Gaudou, B., Herzig, A. & Longin, D. 2006. OCC’s emotions: a formalization in a BDI logic. In International Conference on Artificial Intelligence: Methodology, Systems, and Applications, 24–32. Springer Berlin Heidelberg.CrossRefGoogle Scholar
Adam, C., Herzig, A. & Longin, D. 2009. A logical formalization of the OCC theory of emotions. Synthese 168(2), 201–248.CrossRefGoogle Scholar
Alfonso, B., Vivancos, E. & Botti, V. J. 2014. An open architecture for affective traits in a BDI agent. In Proceedings of the 6th ECTA. Part of the 6th IJCCI, 320–325. SCITEPRESS (Science and Technology Publications, Lda).CrossRefGoogle Scholar
Anderson, J. R. 1993. Rules of the Mind. Lawrence Erlbaum Associates, Inc.Google Scholar
André, E., Klesen, M., Gebhard, P., Allen, S. & Rist, T. 2000. Integrating models of personality and emotions into lifelike characters. In Affective Interactions, 150–165. Springer Berlin Heidelberg.CrossRefGoogle Scholar
Angie, A. D., Connelly, S., Waples, E. P. & Kligyte, V. 2011. The influence of discrete emotions on judgement and decision-making: a meta-analytic review. Cognition & Emotion 25(8), 1393–1422.CrossRefGoogle ScholarPubMed
Becker-Asano, C. 2014. WASABI for affect simulation in human-computer interaction. In Proceeding International Workshop on Emotion Representations and Modelling for HCI Systems.Google Scholar
Becker-Asano, C. & Wachsmuth, I. 2008. Affect simulation with primary and secondary emotions. International Workshop on Intelligent.Google Scholar
Becker-Asano, C. & Wachsmuth, I. 2010. Affective computing with primary and secondary emotions in a virtual human. Autonomous Agents and Multi-Agent Systems 20(20), 32–49.CrossRefGoogle Scholar
Bevacqua, E., Mancini, M. & Pelachaud, C. 2008. A listening agent exhibiting variable behaviour. In International Workshop on Intelligent Virtual Agents. Springer, Berlin, Heidelberg, 262–269.CrossRefGoogle Scholar
Bevacqua, E., Prepin, K., Niewiadomski, R., de Sevin, E. & Pelachaud, C. 2010. Greta: towards an interactive conversational virtual companion. Artificial Companions in Society: Perspectives on the Present and Future 143–156.CrossRefGoogle Scholar
Bickmore, T. W., Utami, D., Matsuyama, R. & Paasche-Orlow, M. K. 2016. Improving access to online health information with conversational agents: a randomized controlled experiment. Journal of Medical Internet Research 18(1), e1.CrossRefGoogle ScholarPubMed
Blanchette, I. & Richards, A. 2010. The influence of affect on higher level cognition: a review of research on interpretation, judgement, decision making and reasoning. Cognition & Emotion 24(4), 561–595.CrossRefGoogle Scholar
Bosse, T. & Höhle, D. 2011. Enhancing believability of virtual soccer players: application of a BDI-model with emotions and trust. In Developing Concepts in Applied Intelligence, Mehrotra, K. G., Mohan, C. O., Jae, C., Varshney, P. K. & Ali, M. (eds). Springer Berlin Heidelberg, 119–128.CrossRefGoogle Scholar
Bosse, T., Jonker, C. M., Van Der Meij, L. & Treur, J. 2007a. A language and environment for analysis of dynamics by simulation. International Journal on Artificial Intelligence Tools 16(3), 435–464.CrossRefGoogle Scholar
Bosse, T. & de Lange, F. P. J. 2008. Development of virtual agents with a theory of emotion regulation. In Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2, 461–468. IEEE Computer Society.CrossRefGoogle Scholar
Bosse, T., Pontier, M. & Treur, J. 2007b. A computational model for adaptive emotion regulation. In Proceedings of the 8th International Conference on Cognitive Modeling, ICCM, 7, 187–192. Taylor and Francis/Psychology Press.Google Scholar
Bosse, T. & Zwanenburg, E. 2009. There’s always hope: enhancing agent believability through expectation-based emotions. In Proceedings – 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009, 1–8. IEEE.CrossRefGoogle Scholar
Boukricha, H. & Wachsmuth, I. 2011. Empathy-based emotional alignment for a virtual human: a three-step approach. KI – Künstliche Intelligenz 25(3), 195–204.CrossRefGoogle Scholar
Bratman, M. 1987. Intention, Plans, and Practical Reason. Harvard University Press.Google Scholar
Braubach, L., Lamersdorf, W. & Pokahr, A. 2003. Jadex: implementing a BDI-infrastructure for JADE. EXP in Search of Innovation 3(3), 76–85.Google Scholar
Breazeal, C. 2002. Designing Sociable Robots. MIT Press.Google Scholar
Breazeal, C. 2003. Emotion and sociable humanoid robots. International Journal of Human–Computer Studies 59(1), 119–155.CrossRefGoogle Scholar
Broekens, J., DeGroot, D. & Kosters, W. A. 2008. Formal models of appraisal: theory, specification, and computational model. Cognitive Systems Research 9(3), 173–197.CrossRefGoogle Scholar
Camerer, C. F., Loewenstein, G. & Rabin, M. 2003. Advances in Behavioral Economics. Princeton University Press.Google Scholar
Canamero, D. 2000. Designing Emotions for Activity Selection. Technical report, University of Aarhus, Denmark.CrossRefGoogle Scholar
Carbonell, J. G. 1980. Towards a process model of human personality traits. Artificial Intelligence 15(1), 49–74.CrossRefGoogle Scholar
Carver, C. S., Scheier, M. F. & Weintraub, J. K. 1989. Assessing coping strategies: a theoretically based approach. Journal of Personality and Social Psychology 56(2), 267.CrossRefGoogle ScholarPubMed
Castelfranchi, C. 2000. Affective appraisal versus cognitive evaluation in social emotions and interactions. In Affective Interactions, Paiva, A. (ed.). Springer Berlin Heidelberg, 70–106.Google Scholar
Castelfranchi, C. & Lorini, E. 2003. Cognitive anatomy and functions of expectations. In IJCAI03 Workshop on Cognitive Modeling of Agents and Multi-Agent Interactions, 9–11. Morgan Kaufmann Publishers.Google Scholar
Cochran, R. E. 2006. Modeling emotion: arousal’s impact on memory. In Proceedings of the 28th Annual Conference of the Cognitive Science Society, 1133–1138. Erlbaum.Google Scholar
Cohen, P. R. & Levesque, H. J. 1990. Intention is choice with commitment. Artificial Intelligence 42(2–3), 213–261.CrossRefGoogle Scholar
Corchado, J. M., Pavón, E. S., Corchado, E. S. & Castillo, L. F. 2004. Development of CBR-BDI agents: a tourist guide application. In European Conference on Case-based Reasoning, 547–559. Springer Berlin Heidelberg.CrossRefGoogle Scholar
Damasio, A. 1994. Descartes’ Error: Emotion, Reason, and the Human Brain. Putnam (Grosset Books).Google Scholar
Damasio, A. R. 2005. Descartes' Error: Emotion, Reason, and the Human Brain. Penguin Group US.Google Scholar
Dastani, M. & Lorini, E. 2012. A logic of emotions: from appraisal to coping. In 11th International Conference on Autonomous Agents and Multiagent Systems, 1133–1140. International Foundation for Autonomous Agents and Multiagent Systems.Google Scholar
Davis, M. H. 1994. Empathy: A Social Psychological Approach. Westview Press.Google Scholar
Desmet, P. 2015. Design for mood: twenty activity-based opportunities to design for mood regulation design. International Journal of Design 9(2), 1–19.Google Scholar
Dias, J., Mascarenhas, S. & Paiva, A. 2014. Fatima modular: towards an agent architecture with a generic appraisal framework. In Emotion Modeling, Bosse, T., Broekens, J., Dias, J. & van der Zwaan, J. M. (eds). Springer International Publishing, 44–56.Google Scholar
D’Inverno, M., Luck, M., Georgeff, M., Kinny, D. & Wooldridge, M. 2004. The DMARS architecture: a specification of the distributed multi-agent reasoning system. Autonomous Agents and Multi-Agent Systems 9(1–2), 5–53.CrossRefGoogle Scholar
Dolan, R. J. 2002. Emotion, cognition, and behavior. Science 298(5596), 1191–1194.CrossRefGoogle Scholar
Durupinar, F., Allbeck, J. M., Pelechano, N. & Badler, N. I. 2008. Creating crowd variation with the OCEAN personality model. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 3.Google Scholar
Van Dyke Parunak, H., Bisson, R., Brueckner, S., Matthews, R. & Sauter, J. 2006. A model of emotions for situated agents. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, 993–995. ACM.CrossRefGoogle Scholar
Ekman, P., Friesen, W. V. & Ellsworth, P. 1972. Emotion in the Human Face: Guidelines for Research and an Integration of Findings. Elsevier.Google Scholar
El-Nasr, M. S., Yen, J. & Ioerger, T. R. 2000. Flame—fuzzy logic adaptive model of emotions. Autonomous Agents and Multi-Agent Systems 3(3), 219–257.CrossRefGoogle Scholar
Emonts, M., Row, R., Johnson, W. L., Thomson, E., De Silva Joyce, H., Gorman, L. G. & Carpenter, R. 2012. Integration of social simulations into a task-based blended training curriculum. In Land Warfare Conference.Google Scholar
Eysenck, H. J. 1967. The Biological Basis of Personality, 689. Transaction Publishers.Google Scholar
Eysenck, H. J. 1991. Dimensions of personality: 16, 5 or 3?—criteria for a taxonomic paradigm. Personality and Individual Differences 12(8), 773–790.CrossRefGoogle Scholar
Folkman, S. & Lazarus, R. S. 1980. An analysis of coping in a middle-aged community sample. Journal of Health and Social Behavior 21(4), 219–239.CrossRefGoogle Scholar
Frijda, N. H. 1986. The Emotions. Cambridge University Press.Google Scholar
Frijda, N. H. 1987. Emotion, cognitive structure, and action tendency. Cognition & Emotion 1(2), 115–143.CrossRefGoogle Scholar
Frijda, N. H., Manstead, A. S. R. & Bem, S. 2000a. The influence of emotions on beliefs. In Emotions and Beliefs: How Feelings Influence Thoughts, Pergamon, 1–9.Google Scholar
Frijda, N. H., Manstead, A. S. R. & Bem, S. (eds) 2000b. Emotions and Beliefs: How Feelings Influence Thoughts. Cambridge University Press.CrossRefGoogle Scholar
Frijda, N. H., Ortony, A., Sonnemans, J. & Clore, G. L. 1992. The complexity of intensity: issues concerning the structure of emotion intensity. In Review of Personality and Social Psychology, No. 13. Emotion, Clark, M. S. (ed.). SAGE Publications, 60–89.Google Scholar
Fum, D. & Stocco, A. 2004. Memory, emotion, and rationality: an ACT-R interpretation for gambling task results. In Proceedings of the 6th International Conference on Cognitive Modeling, 106–111. Lawrence Erlbaum Associates.Google Scholar
Gazzaniga, M. S. & Heatherton, T. F. 2006. Psychological Sciences: Mind, Brain, and Behavior, W.W. Norton.Google Scholar
Gebhard, P. 2005. ALMA – a layered model of affect. In Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systemsent Systems, 29–36. ACM.CrossRefGoogle Scholar
Georgeff, M. P. & Lansky, A. L. 1987. Reactive reasoning and planning. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI-87), 87, 677–682.Google Scholar
Gibson, L. 2006. Mirrored emotion. The University of Chicago Magazine 94(4), 1–9.Google Scholar
Glore, G. L. & Gasper, K. 2000. Feeling is believing: some affective influences on belief. In Emotions and Beliefs: How Feelings Influence Thoughts, Frijda, N. H., Manstead, A. S. R. & Bem, S. (eds). Cambridge University Press, 10–44.CrossRefGoogle Scholar
Gluz, J. & Jaques, P. 2014. A probabilistic implementation of emotional BDI agents. In Proceedings of the 6th International Conference on Agents and Artificial Intelligence, 121–129. SCITEPRESS – Science and and Technology Publications.Google Scholar
Gluz, J. & Jaques, P. A. 2017. A probabilistic formalization of the appraisal for the OCC event-based emotions. Journal of Artificial Intelligence Research 58(1), 627–664.CrossRefGoogle Scholar
Gratch, J. & Marsella, S. 2004. A domain-independent framework for modeling emotion. Cognitive Systems Research 5(4), 269–306.CrossRefGoogle Scholar
Green, O. H. & Green, O. H. 1992. The Emotions: A Philosophical Theory, 53. Springer Science & Business Media.Google Scholar
Gris, I., Rivera, D. A., Rayon, A., Camacho, A. & Novick, D. 2016. Young merlin: an embodied conversational agent in virtual reality. In Proceedings of the 18th ACM International Conference on Multimodal Interaction – ICMI 2016, 425–426. ACM Press.CrossRefGoogle Scholar
Gross, J. J. 1998. The emerging field of emotion regulation: an integrative review. Review of General Psychology 2(5), 271–299.CrossRefGoogle Scholar
Gunes, H., Schuller, B., Pantic, M. & Cowie, R. 2011. Emotion representation, analysis and synthesis in continuous space: a survey. In Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference, 817–834. IEEE.CrossRefGoogle Scholar
Hamburg, M. E., Finkenauer, C. & Schuengel, C. 2014. Food for love: the role of food offering in empathic emotion regulation. Frontiers in Psychology 5(32).CrossRefGoogle Scholar
Hernández, D. J., Déniz, O., Lorenzo, J. & Hernández, M. 2004. BDIE: a BDI like architecture with emotional capabilities. In American Association for Artificial Intelligence Spring Symposium.Google Scholar
Herzig, A. & Longin, D. 2004. C&L intention revisited. In Principles of Knowledge Representation and Reasoning – KR, 527–535.Google Scholar
Hindriks, K. V., De Boer, F. S., Van der Hoek, W. & Meyer, J.-J. Ch. 1999. Agent programming in 3APL. Autonomous Agents and Multi-Agent Systems 2(4), 357–401.CrossRefGoogle Scholar
Hoffman, M. L. 2000. Empathy and Moral Development. Cambridge University Press.CrossRefGoogle Scholar
Huber, M. J. 1999. JAM: a BDI-theoretic mobile agent architecture. In Proceedings of the third annual conference on Autonomous Agents, 236–243. ACM.CrossRefGoogle Scholar
Hudlicka, E. 1998. Modeling emotion within symbolic cognitive architectures. Technical Report FS-98-03, Papers from the 1998 AAAI Fall Symposium.Google Scholar
Hudlicka, E. 2004. Two Sides of Appraisal: Implementing Appraisal and Its Consequences within a Cognitive Architecture. AAAI Press.Google Scholar
Hudlicka, E. 2008. What are we modeling when we model emotion? In AAAI Spring Symposium: Emotion, Personality, and Social Behavior, 8.Google Scholar
Hudlicka, E. 2011. Guidelines for designing computational models of emotions. International Journal of Synthetic Emotions 2(1), 26–79.CrossRefGoogle Scholar
Hughes, G. E. & Cresswell, M. J. 1996. A New Introduction to Modal Logic. Psychology Press.CrossRefGoogle Scholar
Ingrand, F. F., Rao, A. S. & Georgeff, M. P. 1992. An architecture for real-time reasoning and system control. IEEE Expert 7(6), 33–44.CrossRefGoogle Scholar
Izard, C. E. 1993. Four systems for emotion activation: cognitive and noncognitive processes. Psychological Review 100(1), 68–90.CrossRefGoogle ScholarPubMed
Jeon, M. 2017. Emotions and Affect in Human Factors and Human–Computer Interaction. Academic Press.Google Scholar
Jiang, H., Vidal, J. M. & Huhns, M. N. 2007. EBDI: an architecture for emotional agents. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, 5, 11. ACM.CrossRefGoogle Scholar
Jones, H., Saunier, J. & Lourdeaux, D. 2009. Personality, emotions and physiology in a BDI agent architecture: the PEP→BDI model. In Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2, 263–266. IEEE Computer Society.CrossRefGoogle Scholar
Kleinginna, P. R. Jr & Kleinginna, A. M. 1981. A categorized list of emotion definitions, with suggestions for a consensual definition. Motivation and Emotion 5(4), 345–379.CrossRefGoogle Scholar
Kopp, S., Gesellensetter, L., Krämer, N. C. & Wachsmuth, I. 2005. A conversational agent as museum guide – design and evaluation of a real-world application. In International Workshop on Intelligent Virtual Agents, 329–343. Springer Berlin Heidelberg.CrossRefGoogle Scholar
Kuübler-Ross, E. 2009. On Death and Dying: What the Dying Have to Teach Doctors, Nurses, Clergy and Their Own Families. Taylor & Francis.Google Scholar
Laird, J. E., Newell, A. & Rosenbloom, P. S. 1987. Soar: an architecture for general intelligence. Artificial Intelligence 33(1), 1–64.CrossRefGoogle Scholar
Larsen, R. J. 2000. Toward a science of mood regulation. Psychological Inquiry 11(3), 129–141.CrossRefGoogle Scholar
Larsen, R. J. and Ketelaar, T. 1989. Extraversion, neuroticism and susceptibility to positive and negative mood induction procedures. Personality and Individual Differences 10(12), 1221–1228.CrossRefGoogle Scholar
Larsen, R. J. & Ketelaar, T. 1991. Personality and susceptibility to positive and negative emotional states. Journal of Personality and Social Psychology 61(1), 132–140.CrossRefGoogle ScholarPubMed
Lazarus, R. S. 1991. Emotion and Adaptation. Oxford University Press.Google Scholar
Lazarus, R. S. & Folkman, S. 1984. Stress, Appraisal, and Coping. Springer Publishing Co.Google Scholar
LeDoux, J. E. 1996. The Emotional Brain: The Mysterious Underpinnings of Emotional Life. Simon & Schuster.Google Scholar
Lejmi-Riahi, H., Kebair, F. & Said, L. B. 2014. Agent decision-making under uncertainty: towards a new E-BDI agent architecture based on immediate and expected emotions. International Journal of Computer Theory and Engineering 6(3), 254.CrossRefGoogle Scholar
Loewenstein, G. & Lerner, J. 2003. The role of affect in decision making. Handbook of Affective Science 619(642), 3.Google Scholar
Lönnqvist, J. E., Verkasalo, M. & Walkowitz, G. 2001. It pays to pay–big five personality influences on co-operative behaviour in an incentivized and hypothetical Prisoner’s dilemma game. Personality and Individual Differences 50(2), 300–304.CrossRefGoogle Scholar
Marsella, S. C. & Gratch, J. 2009. EMA: a process model of appraisal dynamics. Cognitive Systems Research 10(1), 70–90.CrossRefGoogle Scholar
McCrae, R. R. & John, O. P. 1992. An introduction to the five-factor model and its applications. Journal of Personality 60(2), 175–215.CrossRefGoogle ScholarPubMed
McEachan, R. R. C., Sutton, S. & Myers, L. 2010. Mediation of personality influences on physical activity within the theory of planned behaviour. Journal of Health Psychology 15(8), 1170–1180.CrossRefGoogle ScholarPubMed
McQuiggan, S. W. & Lester, J. C. 2006. Learning empathy: a data-driven framework for modeling empathetic companion agents. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, 961–968, edited by ACM.CrossRefGoogle Scholar
Mehrabian, A. 1996a. Analysis of the big-five personality factors in terms of the PAD temperament model. Australian Journal of Psychology 48(2), 86–92.CrossRefGoogle Scholar
Mehrabian, A. 1996b. Pleasure-arousal-dominance: a general framework for describing and measuring individual differences in temperament. Current Psychology 14(4), 261–292.CrossRefGoogle Scholar
Merenda, P. F. 1987. Toward a four-factor theory of temperament and/or personality. Journal of Personality Assessment 51(3), 367–374.CrossRefGoogle ScholarPubMed
Meyer, J. J. Ch. 2006. Reasoning about emotional agents. International Journal of Intelligent Systems 21(6), 601–619.CrossRefGoogle Scholar
Meyer, J. J. Ch. & Van Der Hoek, W. 2004. Epistemic Logic for AI and Computer Science. Cambridge University Press.Google Scholar
Meyer, J. J. Ch., Van Der Hoek, W. & van Linder, B. 1999. A logical approach to the dynamics of commitments. Artificial Intelligence 113(1), 1–40.CrossRefGoogle Scholar
Moore, R. C. 1980. Reasoning about knowledge and action. In SRI International.CrossRefGoogle Scholar
Morley, D. & Myers, K. 2004. The SPARK agent framework. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2, 714–721. IEEE Computer Society.Google Scholar
Neto, A. F. B. & da Silva, F. S. C. 2012. A computer architecture for intelligent agents with personality and emotions. In Human-Computer Interaction: The Agency Perspective, 263–285. Springer Berlin Heidelberg.CrossRefGoogle Scholar
Neumann, R., Seibt, B. & Strack, F. 2001. The influence of mood on the intensity of emotional responses: disentangling feeling and knowing. Cognition & Emotion 15(6), 725–747.CrossRefGoogle Scholar
Newell, A. 1994. Unified Theories of Cognition. Harvard University Press.Google Scholar
Niedenthal, P. M. & Setterlund, M. B. 1994. Emotion congruence in perception. Personality and Social Psychology Bulletin 20(4), 401–411.CrossRefGoogle Scholar
Nunamaker, Jr , J. F., Derrick, D. C., Elkins, A. C., Burgoon, J. K. & Patton, M. W. 2011. Embodied conversational agent-based kiosk for automated interviewing. Journal of Management Information Systems 28(1), 17–48.CrossRefGoogle Scholar
Oatley, K. & Jenkins, J. M. 1996. Understanding Emotions. Blackwell Publishing.Google Scholar
Ochs, M., Paris, U., Pelachaud, C., Paris, U. & Sadek, D. 2008. An empathic virtual dialog agent to improve human-machine interaction. In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems, 1, 89–96. International Foundation for Autonomous Agents and Multiagent Systems.Google Scholar
Ochs, M., Sadek, D. & Pelachaud, C. 2010. A formal model of emotions for an empathic rational dialog agent. International Journal of Autonomous Agents and Multi-Agent Systems 24(3), 410–440.CrossRefGoogle Scholar
Van Oijen, J., Van Doesburg, W. & Dignum, F. 2011. Goal-based communication using BDI agents as virtual humans in training: an ontology driven dialogue system. In Agents for Games and Simulations II, Lecture Notes in Computer Science, Dignum, F. (ed). Springer Verlag, 38–52.CrossRefGoogle Scholar
Ortony, A. 2002. On making believable emotional agents believable. In Emotions in Humans and Artifacts, Trappl, R., Petta, P. & Payr, S. (eds). The MIT Press, 189–211.Google Scholar
Ortony, A. Clore, , G. L. & Collins, A. 1990. The Cognitive Structure of Emotions. Cambridge University Press.Google Scholar
Pacherie, E. 2004. L’empathie et Ses Degrés. In L’empathie, sous la dir Berthoz, de A. & Jorland, G., 149–181. Editions Odile Jacob.Google Scholar
Paiva, A., Dias, J., Sobral, D., Woods, S. & Hall, L. 2004. Building empathic lifelike characters: the proximity factor. In Workshop on Empathic Agents, AAMAS, 4.Google Scholar
Pereira, D., Oliveira, E., Moreira, N. & Sarmento, L. 2005. Towards an architecture for emotional BDI agents. In EPIA 2005 12th Portuguese Conference on Artificial Intelligence, Universidade da Beira Interior, 40–46. IEEE.CrossRefGoogle Scholar
Pérez, J., Cerezo, E., Serón, F. J. & Rodríguez, L.-F. 2016. A cognitive-affective architecture for ECAs. Biologically Inspired Cognitive Architectures 18, 33–40.CrossRefGoogle Scholar
Plutchik, R. 2001. The nature of emotions. American Scientist 89(4), 344.CrossRefGoogle Scholar
Pollack, M. E. & Ringuette, M. 1990. Introducing the tileworld: experimentally evaluating agent architectures. AAAI 90, 183–189.Google Scholar
Puica, M.-A. & Florea, A.-M. 2013. Emotional belief-desire-intention agent model: previous work and proposed architecture. International Journal of Advanced Research in Artificial Intelligence(IJARAI) 2(2), 1–8.Google Scholar
Rao, A. S. & Georgeff, M. P. 1992. An abstract architecture for rational agents. KR'92, 439–449.Google Scholar
Rao, A. S. 2009. AgentSpeak(L): BDI agents speak out in a logical computable language. In European Workshop on Modelling Autonomous Agents in a Multi-Agent World, 42–55. Springer Berlin Heidelberg.CrossRefGoogle Scholar
Rao, A. S. & Georgeff, M. P. 1995. BDI agents: from theory to practice. Proceedings of the First International Conference on Multiagent Systems (ICMAS95) 95, 312–319.Google Scholar
Van Reekum, C. M. 2000. Levels of Processing in Appraisal: Evidence from Computer Game Generated Emotions. University of Geneva.Google Scholar
Reilly, W. S. 1996. Believable Social and Emotional Agents. PhD thesis, Carnegie Mellon University, School of Computer Science.Google Scholar
Reisenzein, R. 2006. Arnold’s theory of emotion in historical perspective. Cognition and Emotion 20(7), 920–951.CrossRefGoogle Scholar
Reisenzein, R., Hudlicka, E., Dastani, M., Gratch, J., Hindriks, K., Lorini, E. & Meyer, J.-J. Ch. 2013. Computational modeling of emotion: toward improving the inter- and intradisciplinary exchange. IEEE Transactions on Affective Computing 4(3), 246–266.CrossRefGoogle Scholar
Reisenzein, R. & Junge, M. 2012. Language and emotion from the perspective of the computational belief-desire theory of emotion. Dynamicity in Emotion Concepts 27, 37–59.Google Scholar
Remington, N. A., Visser, P. S., Diener, E, Barrett, L. F., Green, D., Mayer, J., Rusting, C. & Watson, D. 2000. Reexamining the circumplex model of affect. Journal of Personality and Social Psychology 79(2), 286–300.CrossRefGoogle Scholar
Roseman, I. J. & Smith, C. 2001. Appraisal Theory: Overview, Assumptions, Varieties, Controversies. In Appraisal Processes in Emotion: Theory, Methods, Research, Oxford University Press, 3–19.Google Scholar
Roseman, I. J., Spindel, M. S. & Jose, P. E. 1990. Appraisals of emotion-eliciting events: testing a theory of discrete emotions. Journal of Personality and Social Psychology 59(5), 899–915.CrossRefGoogle Scholar
Rosenbloom, P. S. 2013. The sigma cognitive architecture and system. AISB Quarterly 136, 4–13.Google Scholar
De Rosis, F., Pelachaud, C., Poggi, I., Carofiglio, V. & De Carolis, B. 2003. From Greta’s mind to her face: modelling the dynamics of affective states in a conversational embodied agent. International Journal of Human–Computer Studies 59(1), 81–118.CrossRefGoogle Scholar
Russell, J. A. 1980. A circumplex model of affect. Journal of Personality and Social Psychology 39(6), 1161–1178.CrossRefGoogle Scholar
Russell, S. J., Norvig, P., Canny, J. F., Malik, J. M. & Edwards, D. D. 2003. Artificial Intelligence: A Modern Approach, 2. Prentice hall.Google Scholar
Scherer, K. R. 1984. On the nature and function of emotion: a component process approach. In Approaches to Emotion, Scherer, K. R. & Ekman, P. E. (eds). Psychology Press, 2293, 317.Google Scholar
Scherer, K. R. 1988. Criteria for emotion-antecedent appraisal: a review. In Cognitive Perspectives on Emotion and Motivation, Hamilton V., Bower G.H. & Frijda N.H. (eds). Springer Netherlands, 89–126.CrossRefGoogle Scholar
Scherer, K. R. 2000. Psychological models of emotion. The Neuropsychology of Emotion 137(3), 137–162.Google Scholar
Scholte, R. H. & De Bruyn, E. E. 2004. Comparison of the giant three and the big five in early adolescents. Personality and Individual Differences 36(6), 1353–1371.CrossRefGoogle Scholar
Schwarz, N. & Clore, G. L. 1983. Mood, misattribution, and judgments of well-being: informative and directive functions of affective states. Journal of Personality and Social Psychology 45(3), 513.CrossRefGoogle Scholar
Serenko, A., Bontis, N. & Detlor, B. 2007. End-user adoption of animated interface agentsin everyday work applications. Behaviour & Information Technology 26(2), 119–132.CrossRefGoogle Scholar
Sherer, K. R. 1999. Appraisal theory. In Handbook of Cognition and Emotion, Dalgleish, T. & Power, M. (eds). John Wiley & Sons Ltd, 637–663.Google Scholar
Sloman, A. 1998. Damasio, Descartes, alarms and meta-management. In SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics, 3 2652–2657.Google Scholar
Sloman, A. 2000. Architectural requirements for human-like agents both natural and artificial (what sorts of machines can love?). In Human Cognition And Social Agent Technology, Advances in Consciousness Research, Dautenhahn, K. (ed). John Benjamins, 163–195.CrossRefGoogle Scholar
Sloman, A. 2002. How many separately evolved emotional beasties live within us? Emotions in Humans and Artifacts 35–114.Google Scholar
Smith, C. A. & Lazarus, R. S. 1991. Emotion and Adaptation. Oxford Univertity.Google Scholar
Soleimani, A. & Kobti, Z. 2012. A mood driven computational model for gross emotion regulation process paradigm. In Proceedings of the World Congress on Engineering, 2.Google Scholar
Steunebrink, B. R., Dastani, M. & Meyer, J. J. Ch. 2012. A formal model of emotion triggers: an approach for BDI Agents. Synthese 185(1), 83–129.CrossRefGoogle Scholar
Van Straalen, B., Heylen, D., Theune, M. & Nijholt, A. 2009. Enhancing embodied conversational agents with social and emotional capabilities. In Agents for Games and Simulations, Dignum, F., Bradshaw, J., Silverman, B.G. & van Doesburg, W. (eds). Springer Berlin Heidelberg, 95–106.CrossRefGoogle Scholar
Thompson, R. A. 1994. Emotion regulation: a theme in search of definition. Monographs of the Society for Research in Child Development 59(2–3), 25–52.CrossRefGoogle ScholarPubMed
Velásquez, J. D. & Maes, P. 1997. Cathexis: a computational model of emotions. In Proceedings of the First International Conference on Autonomous Agents, 518–519. ACM Press.CrossRefGoogle Scholar
De Vignemont, F. & Singer, T. 2006. The empathic brain: how, when and why? Trends in Cognitive Sciences 10(10), 435–441.CrossRefGoogle Scholar
Watson, D. & Tellegen, A. 1985. Toward a consensual structure of mood. Psychological Bulletin 98(2), 219.CrossRefGoogle Scholar
Weiss, G. (ed) 1999. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. MIT Press.Google Scholar
Wiggins, J. S. 2003. Paradigms of Personality Assessment. Guilford Press.Google ScholarPubMed
Winikoff, M. 2005. JackTM intelligent agents: an industrial strength platform. In Multi-Agent Programming, Bordini, R., Dastani. M., Dix, J. & El Fallah Seghrouchni, A. (eds). Springer US, 175–193.Google Scholar
Yu, C. W. & Choi, J. Y. 2005. Behavior decision model based on emotion and dynamic personality. In Proceedings of ICCAS’05, Kintex, Gyeonggi-Do, Korea.Google Scholar
Zadra, J. R. & Clore, G. L. 2011. Emotion and perception: the role of affective information. Wiley Interdisciplinary Reviews. Cognitive Science 2(6), 676–185.CrossRefGoogle ScholarPubMed
Zajonc, R. B., Murphy, S. T. & Inglehart, M. 1989. Feeling and facial efference: implications of the vascular theory of emotion. Psychological Review 96(3), 395.CrossRefGoogle ScholarPubMed