Abstract
Agents, agent-oriented modelling and multi-agent systems (MAS) introduce new and unconventional concepts in computer science. These elements are able to sparkle new modelling perspectives in behavioural knowledge and in environmental domain, where interactions between humans and natural/artificial agents are not standardized. MAS are considered as “societies of agents” interacting to coordinate their behaviour and often cooperate to achieve some collective goal. In order to show the involved agents and their roles in a quasi-hierarchical scale of interaction behaviours, we propose the setting up of schemes aimed at simplifying the behaviors and the interactions between human and non-human agents in indoor spaces for urban microclimate management.
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References
Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, London (1999)
Sandholm, T.W., Lesser, V.R.: Coalition formation among bounded rational agents. In: International Joint Conference on Artificial Intelligence (IJCAI 1995), pp. 662–671. American Association for Artificial Intelligence, Montreal (1995)
O’Hare, G.M.P., Jennings, N. (eds.): Foundations of Distributed Artificial Intelligence. Wiley, London (1996)
Bond, A.H., Gasser, L.G. (eds.): Readings in Distributed Artificial Intelligence. Morgan Kaufmann, San Mateo (1988)
Castelfranchi, C.: Modelling social action for AI agents. Artificial Intelligence 103, 157–182 (1998)
Bobrow, D.G.: Dimensions of interaction. AI Magazine 12, 64–80 (1991)
Ajzen, I.: The theory of planned behavior. Organizational Behavior and Human Decision Processes 50, 179–211 (1991)
Camarda, D.: Cooperative scenario building in environmental planning: Agents, roles, architectures. In: Luo, Y. (ed.) CDVE 2008. LNCS, vol. 5220, pp. 74–83. Springer, Heidelberg (2008)
Borri, D., Camarda, D., Pluchinotta, I.: Planning urban microclimate through multiagent modelling: A cognitive mapping approach. In: Luo, Y. (ed.) CDVE 2013. LNCS, vol. 8091, pp. 169–176. Springer, Heidelberg (2013)
Parsons, S.D., Gymtrasiewicz, P.J., Wooldridge, M.J.: Game Theory and Decision Theory in Agent-Based Systems. Kluwer Academic Publishers, Dordrecht (2002)
Li, J., Sheng, Z., Liu, H.: Multi-agent simulation for the dominant players’ behavior in supply chains. Simulation Modelling Practice and Theory 18, 850–859 (2010)
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Borri, D., Camarda, D., Pluchinotta, I. (2014). Planning for the Microclimate of Urban Spaces: Notes from a Multi-agent Approach. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2014. Lecture Notes in Computer Science, vol 8683. Springer, Cham. https://doi.org/10.1007/978-3-319-10831-5_27
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DOI: https://doi.org/10.1007/978-3-319-10831-5_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10830-8
Online ISBN: 978-3-319-10831-5
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