Academia.eduAcademia.edu

Outline

Special Issue “Multi-Agent Systems”: Editorial

Applied Sciences

https://doi.org/10.3390/APP9050954

Abstract

Multi-agent systems (MAS) allow and promote the development of distributed and intelligent applications in complex and dynamic environments. Applications of this kind have a crucial role in our everyday life, as witnessed by the broad range of domains they are deployed to—such as manufacturing, management sciences, e-commerce, biotechnology, etc. Despite heterogeneity, those domains share common requirements such as autonomy, structured interaction, mobility, and openness—which are well suited for MAS. Therein, in fact, goal-oriented processes can enter and leave the system dynamically and interact with each other according to structured protocols. This special issue gathers 17 contributions spanning from agent-based modelling and simulation to applications of MAS in situated and socio-technical systems.

References (39)

  1. Macal, C.M.; North, M.J. Tutorial on agent-based modeling and simulation. In Proceedings of the 37th Winter Simulation Conference, Orlando, FL, USA, 4-7 December 2005; p. 14, doi:10.1109/WSC.2005.1574234. [CrossRef]
  2. Weyns, D.; Holvoet, T. A formal model for situated multi-agent systems. Fundam. Inf. 2004, 63, 125-158.
  3. Suchman, L.A. Plans and Situated Actions: The Problem of Human-Machine Communication; Cambridge University Press: New York, NY, USA, 1987.
  4. Whitworth, B. Socio-technical systems. Encycl. Hum. Comput. Interact. 2006, 533-541.
  5. Berners-Lee, T.; Hendler, J.; Lassila, O. The semantic web. Sci. Am. 2001, 284, 34-43. [CrossRef]
  6. Zhang, Q.; Yao, J.; Yin, Q.; Zha, Y. Learning behavior trees for autonomous agents with hybrid constraints evolution. Appl. Sci. 2018, 8, 1077, doi:10.3390/app8071077. [CrossRef]
  7. Miyashita, K. Incremental design of perishable goods markets through multi-agent simulations. Appl. Sci. 2017, 7, 1300, doi:10.3390/app7121300. [CrossRef]
  8. García-Magariño, I.; Lombas, A.S.; Plaza, I.; Medrano, C. ABS-SOCI: An agent-based simulator of student sociograms. Appl. Sci. 2017, 7, 1126, doi:10.3390/app7111126. [CrossRef]
  9. Raya-Díaz, K.; Gaxiola-Pacheco, C.; Castañón-Puga, M.; Palafox, L.E.; Castro, J.R.; Flores, D.L. Agent-based model for automaticity management of traffic flows across the network. Appl. Sci. 2017, 7, 928, doi:10.3390/app7090928. [CrossRef]
  10. IBM. An Architectural Blueprint for Autonomic Computing; Technical Report; IBM: Armonk, NY, USA, 2005.
  11. Shang, Y. On the delayed scaled consensus problems. Appl. Sci. 2017, 7, 713, doi:10.3390/app7070713. [CrossRef]
  12. Roy, S. Scaled consensus. Automatica 2015, 51, 259-262, doi:10.1016/j.automatica.2014.10.073. [CrossRef]
  13. Duan, K.; Fong, S.; Zhuang, Y.; Song, W. Artificial neural networks in coordinated control of multiple hovercrafts with unmodeled terms. Appl. Sci. 2018, 8, 862, doi:10.3390/app8060862. [CrossRef]
  14. Jordán, J.; Palanca, J.; del Val, E.; Julian, V.; Botti, V. A multi-agent system for the dynamic emplacement of electric vehicle charging stations. Appl. Sci. 2018, 8, 313, doi:10.3390/app8020313. [CrossRef]
  15. Lozano, Á.; De Paz, J.F.; Villarrubia González, G.; Iglesia, D.H.D.L.; Bajo, J. Multi-agent system for demand prediction and trip visualization in bike sharing systems. Appl.Sci. 2018, 8, 67, doi:10.3390/app8010067. [CrossRef]
  16. Hussain, I.; Khan, M.A.; Baqueri, S.F.A.; Shah, S.A.R.; Bashir, M.K.; Khan, M.M.; Khan, I.A. An organizational-based model and agent-based simulation for co-traveling at an aggregate level. Appl. Sci. 2017, 7, 1221, doi:10.3390/app7121221. [CrossRef]
  17. Cossentino, M.; Gaud, N.; Hilaire, V.; Galland, S.; Koukam, A. ASPECS: An agent-oriented software process for engineering complex systems. Auton. Agents Multi-Agent Syst. 2010, 20, 260-304, doi:10.1007/s10458-009-9099-4. [CrossRef]
  18. Zuhaib, K.M.; Khan, A.M.; Iqbal, J.; Ali, M.A.; Usman, M.; Ali, A.; Yaqub, S.; Lee, J.Y.; Han, C. Collision avoidance from multiple passive agents with partially predictable behavior. Appl. Sci. 2017, 7, 903, doi:10.3390/app7090903. [CrossRef]
  19. Van den Berg, J.; Snape, J.; Guy, S.J.; Manocha, D. Reciprocal collision avoidance with acceleration-velocity obstacles. In Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, 9-13 May 2011; pp. 3475-3482, doi:10.1109/ICRA.2011.5980408. [CrossRef]
  20. Wilkie, D.; van den Berg, J.; Manocha, D. Generalized velocity obstacles. In Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA, 10-15 October 2009; pp. 5573-5578, doi:10.1109/IROS.2009.5354175. [CrossRef]
  21. Billhardt, H.; Fernández, A.; Lujak, M.; Ossowski, S. Agreement technologies for coordination in smart cities. Appl. Sci. 2018, 8, 816, doi:10.3390/app8050816. [CrossRef]
  22. Ramos, J.; Oliveira, T.; Satoh, K.; Neves, J.; Novais, P. Cognitive assistants-An analysis and future trends based on speculative default reasoning. Appl. Sci. 2018, 8, 742, doi:10.3390/app8050742. [CrossRef]
  23. Baldoni, M.; Baroglio, C.; May, K.M.; Micalizio, R.; Tedeschi, S. Computational accountability in MAS organizations with ADOPT. Appl. Sci. 2018, 8, 489, doi:10.3390/app8040489. [CrossRef]
  24. Castelfranchi, C. Commitments: From Individual Intentions to Groups and Organizations; ICMAS: Maryville, TN, USA, 1995; Volume 95, pp. 41-48.
  25. Foundation for Intelligent Physical Agents. FIPA Contract Net Interaction Protocol Specification; Foundation for Intelligent Physical Agents: Geneva, Switzerland, 2002.
  26. Boissier, O.; Bordini, R.H.; Hübner, J.F.; Ricci, A.; Santi, A. Multi-agent oriented programming with JaCaMo. Sci. Comput. Programm. 2013, 78, 747-761, doi:10.1016/j.scico.2011.10.004. [CrossRef]
  27. Bordini, R.H.; Hübner, J.F.; Wooldridge, M.J. Programming Multi-Agent Systems in AgentSpeak Using Jason; Wiley: Hoboken, NJ, USA, 2007.
  28. Ricci, A.; Piunti, M.; Viroli, M.; Omicini, A. Environment programming in CArtAgO. In Multi-Agent Programming: Languages, Tools and Applications; El Fallah Seghrouchni, A., Dix, J., Dastani, M., Bordini, R.H., Eds.; Springer: Boston, MA, USA, 2009; pp. 259-288, doi:10.1007/978-0-387-89299-3_8.
  29. Rosales, R.; Castañón-Puga, M.; Lara-Rosano, F.; Flores-Parra, J.M.; Evans, R.; Osuna-Millan, N.; Gaxiola-Pacheco, C. Modelling the interaction levels in HCI using an intelligent hybrid system with interactive agents: A case study of an interactive museum exhibition module in Mexico. Appl. Sci. 2018, 8, 446, doi:10.3390/app8030446. [CrossRef]
  30. Gayesky, D.; Williams, D. Interactive video in higher education. In Video in Higher Education; Kogan Page: London, UK, 1984.
  31. Barriuso, A.L.; De la Prieta, F.; Villarrubia González, G.; De La Iglesia, D.H.; Lozano, Á. MOVICLOUD: Agent-based 3D platform for the labor integration of disabled people. Appl. Sci. 2018, 8, 337, doi:10.3390/app8030337. [CrossRef]
  32. Bellifemine, F.L.; Poggi, A.; Rimassa, G. JADE-A FIPA-compliant agent framework. In Proccedings of the 4th International Conference and Exhibition on the Practical Application of Intelligent Agents and Multi-Agent Technology (PAAM-99); The Practical Application Company Ltd.: London, UK, 1999; pp. 97-108.
  33. Rao, A.S.; Georgeff, M.P. Modeling rational agents within a BDI-architecture. In Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning; Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 1991; pp. 473-484.
  34. Boztepe, ˙I.S.; Erdur, R.C. Linked data aware agent development framework for mobile devices. Appl. Sci. 2018, 8, 1831, doi:10.3390/app8101831. [CrossRef]
  35. Berners-Lee, T. Personal View on Linked Data for Semantic Web: Architectural Design Issues. Available online: https://www.w3.org/DesignIssues/LinkedData.html (accessed on 5 March 2019).
  36. Challenger, M.; Tezel, B.T.; Alaca, O.F.; Tekinerdogan, B.; Kardas, G. Development of semantic web-enabled BDI multi-agent systems using SEA_ML: An electronic bartering case study. Appl. Sci. 2018, 8, 688, doi:10.3390/app8050688. [CrossRef]
  37. Pokahr, A.; Braubach, L.; Lamersdorf, W. Jadex: A BDI reasoning engine. In Multi-Agent Programming: Languages, Platforms and Applications; Bordini, R.H., Dastani, M., Dix, J., El Fallah Seghrouchni, A., Eds.; Springer: Boston, MA, USA, 2005; pp. 149-174, doi:10.1007/0-387-26350-0_6.
  38. Howden, N.; Ronnquist, R.; Hodgson, A.; Lucas, A. Jack intelligent agents-summary of an agent infrastructure. In Proceedings of the 5th International Conference on Autonomous Agents, Montreal, QC, Canada, 28 May-1 June 2001.
  39. Roman, D.; Keller, U.; Lausen, H.; de Bruijn, J.; Lara, R.; Stollberg, M.; Polleres, A.; Feier, C.; Bussler, C.; Fensel, D. Web service modeling ontology. Appl. Ontol. 2005, 1, 77-106.