Abstract
We explore a means to understand second order emergent social phenomena (EP2), that is, phenomena that involve groups of agents who reason and decide, specifically, about actions – theirs or others’ – that may affect the social environment where they interact with other agents. We propose to model such phenomena as socio-cognitive technical systems that involve, on one hand, agents that are imbued with social rationality (thus socio-cognitive) and, on the other hand, a social space where they interact. For that modelling we rely on the WIT framework that defines such socio-cognitive technical systems as a trinity of aspects (the social phenomenon, the simulation model and the implementation of that model). In this paper we centre our attention on the use of affordances as a useful construct to model socio-cognitive technical systems. We use the example of reputation emergence to illustrate our proposal.
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Notes
- 1.
COIN is the acronym Coordination, Organisations, Institutions and Norms, which has been adopted by a community of researchers, mostly within multiagent systems, who focus on these four topics. The COIN community typically organises two workshops each year leading to an annual volume of collected papers, published by Springer LNCS. The first COIN workshop took place in 2005 alongside AAMAS in Utrecht.
- 2.
We mean exogenous events that affect the behaviour of the system in a relevant way and should therefore be accounted for in the description and implementation of the system. For example, rainfall, a new exchange rate, the passage of time.
- 3.
In Notion 4 we postulate that the views are coherent when they are sort of isomorphic. This is an elusive concept in the sense that unless one has a precise specification of each view it is impossible to define the intended “bijections”. However, the alignment can be made precise when one has a precise description of the domain language used in \(\mathcal {W}\), the corresponding action, norm and communication languages used in \(\mathcal {I}\); and, in turn how those are transcribed into actual code in \(\mathcal {T}\) through some specification language. See [7, 12] for an example.
- 4.
Experimental data inputs consist of an initial state—including a population of agents with their own profiles and data—that is uploaded into \(\mathcal {P}\), and then events—generated somehow—and actions taken by agents. By extension, the presence of human actors in \(\mathcal {V}\) would make this a participatory simulation.
- 5.
See Sect. 4 for a more detailed list.
- 6.
In [22] we elaborated on the convenience of separating design (\(\mathcal {M}\)) and implementation (\(\mathcal {P}\)) concerns and also the advantage of building a metamodel that facilitates design and a corresponding platform that supports implementation. We also discussed the advantage of having a “design environment” to deal separately with the definition and management of simulations.
- 7.
When we talk about social simulation we have to talk invariably about agent-based social simulation (ABSS). The main characteristic of a social simulation is that the simulated individuals are not entities whose aggregated behaviour can be adequately described using mathematical equations. Every individual is unique and interacts with the other individuals and the environment in an autonomous way. This particularity is what makes the multiagent systems paradigm the predominant approach in social simulation nowadays. From now on, we will use the terms social simulation and agent-based social simulation interchangeably.
- 8.
We only make reference to Schelling’s dynamics example for sake of reader familiarity, rather than to engage in debate about its appropriateness or correctness.
References
Aldewereld, H., Boissier, O., Dignum, V., Noriega, P., Padget, J. (eds.): Social Coordination Frameworks for Social Technical Systems. LGTS, vol. 30. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-33570-4
Castelfranchi, C.: Cognitive architecture and contents for social structures and interactions. In: Sun, R. (ed.) Cognition and Multi-agent Interaction, pp. 355–390. Cambridge University Press, Cambridge (2006)
Castelfranchi, C.: InMind and OutMind; Societal Order Cognition and Self-Organization: The role of MAS, May 2013. http://www.slideshare.net/sleeplessgreenideas/castelfranchi-aamas13-v2. Invited talk for the IFAAMAS “Influential Paper Award”. AAMAS 2013. Saint Paul, Minn. US
Coleman, J.S.: Foundations of Social Theory. Belknap Press, Cambridge (1990)
Conte, R., Andrighetto, G., Campennì, M., Paolucci, M.: Emergent and immergent effects in complex social systems. In: Proceedings of AAAI Symposium, Social and Organizational Aspects of Intelligence, pp. 8–11 (2007)
Dennett, D.: The Intentional Stance. MIT Press, Cambridge (1989)
d’Inverno, M., Luck, M., Noriega, P., Rodriguez-Aguilar, J.A., Sierra, C.: Communicating open systems. Artif. Intell. 186, 38–94 (2012)
Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2006)
Esteva, M., Padget, J., Sierra, C.: Formalizing a language for institutions and norms. In: Meyer, J.-J.C., Tambe, M. (eds.) ATAL 2001. LNCS (LNAI), vol. 2333, pp. 348–366. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45448-9_26
Harbers, M., van den Bosch, K., Meyer, J.-J.: Modeling agents with a theory of mind: theory-theory versus simulation theory. Web Intell. Agent Syst. 10(3), 331–343 (2012)
Jones, A.J.I., Artikis, A., Pitt, J.: The design of intelligent socio-technical systems. Artif. Intell. Rev. 39(1), 5–20 (2013)
Noriega, P., de Jonge, D.: Electronic institutions: the EI/EIDE framework. In: Aldewereld, H., Boissier, O., Dignum, V., Noriega, P., Padget, J. (eds.) Social Coordination Frameworks for Social Technical Systems. LGTS, vol. 30, pp. 47–76. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-33570-4_4
Noriega, P., Padget, J., Verhagen, H., d’Inverno, M.: Towards a framework for socio-cognitive technical systems. In: Ghose, A., Oren, N., Telang, P., Thangarajah, J. (eds.) COIN 2014. LNCS (LNAI), vol. 9372, pp. 164–181. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25420-3_11
Noriega, P., Verhagen, H., d’Inverno, M., Padget, J.: A manifesto for conscientious design of hybrid online social systems. In: Cranefield, S., Mahmoud, S., Padget, J., Rocha, A.P. (eds.) COIN-2016. LNCS (LNAI), vol. 10315, pp. 60–78. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66595-5_4
Norman, D.A.: Affordance, conventions, and design. interactions 6(3), 38–43 (1999)
Padget, J., ElDeen Elakehal, E., Li, T., De Vos, M.: InstAL: an institutional action language. In: Aldewereld, H., Boissier, O., Dignum, V., Noriega, P., Padget, J. (eds.) Social Coordination Frameworks for Social Technical Systems. LGTS, vol. 30, pp. 101–124. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-33570-4_6
Pinyol, I., Paolucci, M., Sabater-Mir, J., Conte, R.: Beyond accuracy. reputation for partner selection with lies and retaliation. In: Antunes, L., Paolucci, M., Norling, E. (eds.) MABS 2007. LNCS (LNAI), vol. 5003, pp. 128–140. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70916-9_10
Pinyol, I., Sabater-Mir, J.: Computational trust and reputation models for open multi-agent systems: a review. Artif. Intell. Rev. 40(1), 1–25 (2013)
Ruben, D.H.: The existence of social entities. Philos. Q. 32, 295–310 (1982)
Searle, J.R.: What is an institution? J. Inst. Econ. 1(01), 1–22 (2005)
Sun, R.: Desiderata for cognitive architectures. Philos. Psychol. 17(3), 341–373 (2004)
Verhagen, H., Noriega, P., d’Inverno, M.: Towards a design framework for controlled hybrid social games. In: Verhagen, H., Noriega, P., Balke, T., de Vos, M. (eds.) Social Coordination: Principles, Artefacts and Theories (SOCIAL.PATH), AISB 2013 Convention Proceedings, Exeter, UK, 3 April 2013, pp. 83–87. The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (2013)
Acknowledgements
This research has been supported by project MILESS (Ministerio de economía y competitividad - TIN2013-45039-P - financed by FEDER) and SCAR project (Ministerio de economía y competitividad - TIN2015-70819-ERC). We also thank the Generalitat de Catalunya (Grant: 2014 SGR 118).
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Noriega, P., Sabater-Mir, J., Verhagen, H., Padget, J., d’Inverno, M. (2017). Identifying Affordances for Modelling Second-Order Emergent Phenomena with the \(\mathcal {WIT}\) Framework. In: Sukthankar, G., Rodriguez-Aguilar, J. (eds) Autonomous Agents and Multiagent Systems. AAMAS 2017. Lecture Notes in Computer Science(), vol 10643. Springer, Cham. https://doi.org/10.1007/978-3-319-71679-4_14
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