Abstract
Agent-based modeling and simulation are some powerful techniques that are widely used with success for analyzing complex and emergent phenomena in many research and application areas. Many different reasons are behind the success of such techniques, among which an important mention goes to the availability of a great variety of software tools, that ease the development of models, as well as the execution of simulations and the analysis of results. However, the agent models provided by such tools do not offer the features of the computational agents found in multi-agent systems or distributed artificial intelligence techniques. Therefore, it is difficult to use such tools to model complex systems defined by autonomous, proactive and social entities. This paper presents an actor software library, called ActoDeS, for the development of concurrent and distributed systems, and shows how it can be a suitable mean for building flexible and scalable ABMS applications.
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References
Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., Balan, G.: MASON: a multi-agent simulation environment. Simulation 82(7), 517–527 (2005)
Tisue, S., Wilensky, U.: Netlogo: a simple environment for modeling complexity. In: Proceedings of ICCS 2004, Boston, MA, USA, pp. 16–21 (2004)
North, M.J., Collier, N., Vos, J.: Experiences in creating three implementations of the repast agent modeling toolkit. ACM Trans. Model. Comput. Simul. 16(1), 1–25 (2006)
Drogoul, A., Vanbergue, D., Meurisse, T.: Multi-agent based simulation: where are the agents? In: Sichman, J.S., Bousquet, F., Davidsson, P. (eds.) MABS 2002. LNCS (LNAI), vol. 2581, pp. 1–15. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-36483-8_1
De Chiara, R., Mancuso, A., Mazzeo, D., Scarano, V., Spagnuolo, C.: Bringing together efficiency and effectiveness in distributed simulations: the experience with D-MASON. Simulation 89(10), 1236–1253 (2013)
Cicirelli, F., Furfaro, A., Giordano, A., Nigro, L.: HLA_ACTOR_REPAST: an approach to distributing repast models for high-performance simulations. Simul. Model. Pract. Theory 19(1), 283–300 (2011)
Agha, G.A.: Actors: a model of concurrent computation in distributed systems (1986)
Kafura, D., Briot, J.P.: Actors and agents. IEEE Concurrency 6(2), 24–29 (1998)
Jang, M.W., Agha, G.A.: Agent framework services to reduce agent communication overhead in large-scale agent-based simulations. Simul. Model. Pract. Theory 14(6), 679–694 (2006)
Mathieu P., Yann, S.: Environment updating and agent scheduling policies in agent-based simulators. In: Proceedings of ICAART, pp. 170–175 (2012)
Gardner, M.: The fantastic combinations of John Conway’s new solitaire game Life. Sci. Am. 223, 120–123 (1970)
Bergenti, F., Franchi, E., Poggi, A.: Agent-based interpretations of classic network models. Comput. Math. Organ. Theory 19(2), 105–127 (2013)
Franchi, E., Poggi, A., Tomaiuolo, M.: Blogracy: a peer-to-peer social network. Int. J. Distrib. Syst. Technol. 7(2), 37–56 (2016)
Benda, M.: On optimal cooperation of knowledge sources: an empirical investigation. Technical report, Boeing Advanced Technology Center (1986)
Nagel, K., Wolf, D.E., Wagner, P., Simon, P.: Two-lane traffic rules for cellular automata: a systematic approach. Phys. Rev. E 58(2), 1425–1437 (1998)
Reynolds, C.W.: Flocks, herds and schools: a distributed behavioral model. ACM SIGGRAPH Comput. Graph. 21(4), 25–34 (1987)
Alon, N., Kleitman, D.J.: Partitioning a rectangle into small perimeter rectangles. Discrete Math. 103(2), 111–119 (1992)
Bergenti, F., Poggi, A., Tomaiuolo, M.: An actor based software framework for scalable applications. In: Fortino, G., Di Fatta, G., Li, W., Ochoa, S., Cuzzocrea, A., Pathan, M. (eds.) IDCS 2014. LNCS, vol. 8729, pp. 26–35. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11692-1_3
Pax, R., Pavón, J.: Agent architecture for crowd simulation in indoor environments. J. Ambient Intell. Humaniz. Comput. 8(2), 205–212 (2017)
Bergenti, F., Iotti, E., Monica, S., Poggi, A.: Agent-oriented model-driven development for JADE with the JADEL programming language. Comput. Lang. Syst. Struct. 50, 142–158 (2017)
Negri, A., Poggi, A., Tomaiuolo, M., Turci, P.: Dynamic grid tasks composition and distribution through agents. Concurrency Comput. Pract. Exp. 18(8), 875–885 (2005)
Franchi, E., Poggi, A., Tomaiuolo, M.: Social media for online collaboration in firms and organizations. Int. J. Inf. Syst. Model. Des. 7(1), 18–31 (2016)
Bergenti, B., Poggi, A.: An agent-based approach to manage negotiation protocols in flexible CSCW systems: In: Proceedings of 4th International Conference on Autonomous Agents, pp. 267–268 (2000)
Poggi, A., Tomaiuolo, M., Vitaglione, G.: A security infrastructure for trust management in multi-agent systems. In: Falcone, R., Barber, S., Sabater-Mir, J., Singh, Munindar P. (eds.) TRUST 2003-2004. LNCS (LNAI), vol. 3577, pp. 162–179. Springer, Heidelberg (2005). https://doi.org/10.1007/11532095_10
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Angiani, G., Fornacciari, P., Lombardo, G., Poggi, A., Tomaiuolo, M. (2018). Actors Based Agent Modelling and Simulation. In: Bajo, J., et al. Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection. PAAMS 2018. Communications in Computer and Information Science, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-319-94779-2_38
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